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Since H.264/A VC achieves a high compression atio by reducing spatio-temporal redundancy in video equences, the payload of a single packet can often contain a vhole frame encoded by H.264/AVC. Therefore, the loss of a ingle packet does not only cause the loss of a whole frame, `ut also produce error propagation into succeeding frames. ~o deal with this problem, in this paper, we propose a novel ~rame error concealment method for ff264/A VC. First, the iroposed method extrapolates motion vectors from available reighboring frames onto the lost frame. Then, inter-modes of rh macroblocks in the lost frame are adaptively estimated by rsing the extrapolated motion vectors and features of 1.264/A VC. Experimental results exhibit that the proposed ~iethod outperforms the conventional methods in terms of roth objective and subjective video quality. [ABSTRACT FROM AUTHOR]

This paper presents an integrated color imaging system for taking images in extremely high dynamic range scenes. The system first fuses several differently exposed raw images to acquire more intensity information. The effective dynamic range of the image raw data can be extended to 256 times ~five differently exposed images are fused. Then it runs edge detection iterations to extract the image details in different luminance levels. The proposed tone reproduction algorithm equalizes the histogram of the extracted fine edges which tends to assign larger dynamic range for highly populated regions. Finally, the local contrast enhancement is performed to further refine the image details. The experimental results show that the proposed high dynamic range imaging system has good performance on both tone and color reproduction'. [ABSTRACT FROM AUTHOR]

Lighting consumes the largest amount of energy in buildings. Recently, many studies of energy-efficient lighting systems with a variety of sensor and communication technologies have been conducted as a way to increase the cost efficiency of lighting. However, earlier studies have mostly focused on energy efficiency, whereas they have not significantly considered the occupant’s satisfaction. Therefore, this paper proposes an energy-saving lighting control system considering the occupant’s satisfaction. The proposed system improves the energy efficiency and the occupant’s satisfaction by controlling lighting control parameters considering the characteristics of space and the occupant’s behavior patterns. Moreover, this paper deployed the proposed lighting systems in a building and operated them in a real work environment to evaluate the performance. The results showed that the proposed system reduced energy consumption up to 43% by replacing the existing fluorescent lights with the proposed lighting control systems. [ABSTRACT FROM PUBLISHER]

The energy consumption of consumer electronic (CE) devices during media playback is inexorably linked to the computational complexity of decoding compressed video. Reducing a CE device’s the energy consumption is therefore becoming ever more challenging with the increasing video resolutions and the complexity of the video coding algorithms. To this end, this paper proposes a framework that alters the video bit stream to reduce the decoding complexity and simultaneously limits the impact on the coding efficiency. In this context, this paper first performs an analysis to determine the tradeoff between the decoding complexity, video quality, and bit rate with respect to a reference decoder implementation on a general purpose processor architecture. Thereafter, a novel generic decoding complexity-aware video coding algorithm is proposed to generate decoding complexity–rate–distortion optimized High Efficiency Video Coding (HEVC) bit streams. The experimental results reveal that the bit streams generated by the proposed algorithm achieve 29.43% and 13.22% decoding complexity reductions for a similar video quality with minimal coding efficiency impact compared to the state-of-the-art approaches when applied to the HM16.0 and openHEVC decoder implementations, respectively. In addition, analysis of the energy consumption behavior for the same scenarios reveal up to 20% energy consumption reductions while achieving a similar video quality to that of HM 16.0 encoded HEVC bit streams. [ABSTRACT FROM PUBLISHER]

High-performance multicast packet switching technologies are evolving to meet the growing demand for scalability on the Internet and datacenters, etc. Implementing a high-performance switch/router relies on a polynomial-time group membership query algorithm within the Packet Forwarding Engines (PFEs) to determine whether a packet is forwarded through an egress. Among these, Bloom filter (BF)-based and Residue Number System (RNS)-based are being considered as two representatives of the membership query algorithms. However, both approaches suffer from some fatal weaknesses such as false-positive probability and time inefficiencies, especially for a carrier-grade PFE with high port-density features. According to similar properties of the RNS, we propose a simplified forwarding algorithm in this paper, named Per-Port Prime Filter Array (P3FA). The simulation results indicate that the P3FA can significantly improve space efficiencies under specific lower egress-diversities conditions. Under the same space constraints, P3FA improves multicast and unicast time efficiency by 1 to 4 orders of magnitude in the port-density 16–1024 range compared to previous works. Although it comes at the expense of hardware cost, it is still acceptable compared to recently improved previous work. [ABSTRACT FROM AUTHOR]

This paper presents a nonintrusive load monitoring (NILM) algorithm based on mixed-integer linear programming. The formulation deals with the problem of multiple switching that arises when disaggregating individual appliance’s consumptions from a compound power measurement. Mixed-integer linear constraints are used to efficiently represent the load signatures of each appliance. Also, a window-based strategy is used to enhance the computational performance of the proposed NILM algorithm. The disaggregation can be made using only active power measurements at a low sampling rate, which is available in most energy meters. Moreover, if available, other signatures can be added to the model to improve its accuracy, such as reactive power signatures or harmonics. The performance of the algorithm is evaluated using three test cases from the almanac of minutely power dataset. The proposed method is also compared with a disaggregation method called aided linear integer programming. Results demonstrate the ability of the proposed method to accurately identify and allocate individual energy signatures in a computationally efficient manner, which makes it suitable for inexpensive home energy management. [ABSTRACT FROM AUTHOR]

This paper presents low-cost compressors for video display systems, which compress video data to reduce the size of the frame memory in a display panel in a television or a smartphone. The hardware solution exploits the discrete wavelet transform (DWT) and 1-D set partitioning in hierarchical trees (SPIHT) to support the raster-scan processing order in a display system and meet the fixed target compression ratio (CR). However, the compression efficiency and hardware cost often increase in proportion to the block size and thus, designing a compressor with low cost but high fidelity is challenging. This paper proposes a generic partitioned SPIHT algorithm, which achieves a low-cost design for mobile devices by allowing various sizes of partitioned sub-blocks. By taking advantage of DWT decomposition properties, the proposed algorithm partitions a coding block into sub-blocks, each of which can be processed independently. The independent coding operations among multiple sub-blocks allow the size of the hardware buffer to be decreased, by storing the temporary results only for an individual sub-block. However, the proposed sub-block coding slightly decreases the compression efficiency when each sub-block is compressed with the same target CR. To reduce the drop-off in the compression efficiency, the boundary-pixel handling in DWT is exploited and the proposed partitioned SPIHT method adjusts the target CR for each sub-block depending on the potential quality loss. When compared with the previous 1-D design, experimental results show that the hardware gate count and internal memory are reduced by 59.34% and 75%, respectively. Furthermore, the proposed boundary handling and bit-allocation schemes mitigate the PSNR degradation due to the sub-block coding by 1.11 dB. [ABSTRACT FROM PUBLISHER]

To help the blind people walk to the destination efficiently and safely in indoor environment, a novel wearable navigation device is presented in this paper. The locating, way-finding, route following, and obstacle avoiding modules are the essential components in a navigation system, while it remains a challenging task to consider obstacle avoiding during route following, as the indoor environment is complex, changeable, and possibly with dynamic objects. To address this issue, we propose a novel scheme which utilizes a dynamic subgoal selecting strategy to guide the users to the destination and help them bypass obstacles at the same time. This scheme serves as the key component of a complete navigation system deployed on a pair of wearable optical see-through glasses for the ease of use of blind people’s daily walks. The proposed navigation device has been tested on a collection of individuals and proved to be effective on indoor navigation tasks. The sensors embedded are of low cost, small volume, and easy integration, making it possible for the glasses to be widely used as a wearable consumer device. [ABSTRACT FROM PUBLISHER]

Low power hardware acceleration cores for integration into real-time High Efficiency Video Coding (HEVC) codec for smartphones, tablets, camcorders, and televisions are in great demand. This need motivates one for an efficient realization of Discrete Cosine Transform (DCT) and Inverse-DCT (IDCT) for HEVC. This paper presents an algorithm to calculate the required minimum number of low-frequency DCT-output/IDCT-input coefficients for 4, 8, 16, and 32-point DCT/IDCT in HEVC, such that there is a slight decrease in peak-signal-to-noise-ratio (<0.15 decibel) and a minor increment in bitrate (<1.5%) as compared to the reference HEVC-Test-Model (HM) Software. However, the encoding time gets reduced at most by 17.95% for Class-A type sequences, while reporting mean-squared-error and structural-similarity of 1.42 and 0.9913, respectively for 4K ultra-high-definition videos. Moreover, HEVC-compliant computationally efficient architectures are introduced for n-point DCT/IDCT. The presented flexible Transpose Memory architecture uses only sixteen random-access-memories to support all transform-unit sizes in HEVC. The proposed two-dimensional DCT/IDCT architecture can process up to 288@ $4K$ frames-per-second, and it consumes the minimum power, energy, and area of 11.23 milliwatts, 2.34 picojoules, and 120 kilo-gate-equivalents, respectively. Such design with low power, area, and energy features can be included in a real-time HEVC codec for HEVC-compliant consumer electronic devices. [ABSTRACT FROM AUTHOR]

Consumer Electronics (CE) devices have started to support 360° videos in order to improve the perceived video quality by consumers. Higher compression in 360° videos not only lead to improved consumer perception, but also efficient energy and storage usage in CE devices. Consequently, efficient compression of such video content is becoming a critical design consideration of CE devices. To this end, this paper first proposes a residual weighting algorithm that utilizes the features of Weighted Craster Parabolic Projection Peak Signal-to-Noise Ratio (WCPPPSNR), to instigate the first stage of magnitude reduction of the residuals. The model parameters associated with the residual weighting algorithm are determined in the initial experimental stage. Next, the paper proposes a Quantization Parameter (QP) optimization technique which introduces the second stage of magnitude reduction for residuals with minimal impact on the overall video quality. The proposed method is tested on the Versatile Video Coding (VVC) test model with All-Intra configuration. In this context, the empirical results demonstrate that the proposed method improves the coding efficiency by 3.34% on average and outperforms the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

In professional/consumer domains, video databases are broadly applied, facilitating quick searching by fast region analysis, to provide an indication of the video contents. For realtime and cost-efficient implementations, it is important to develop algorithms with high accuracy and low computational complexity. In this paper, we analyze the accuracy and computational complexity of newly developed approaches for semantic region labeling and salient region detection, which aim at extracting spatial contextual information from a video. Both algorithms are analyzed by their native DSP computations and memory usage to prove their practical feasibility. In the analyzed semantic region labeling approach, color and texture features are combined with their related vertical image position to label the key regions. In the salient region detection approach, a discrete cosine transform (DCT) is employed, since it provides a compact representation of the signal energy and the computation can be implemented at low cost. The techniques are applied to two complex surveillance use cases, moving ships in a harbor region and moving cars in traffic surveillance videos, to improve scene understanding in surveillance videos. Results show that our spatial contextual information methods quantitatively and qualitatively outperform other approaches with up to 22% gain in accuracy, while operating at several times lower complexity. [ABSTRACT FROM AUTHOR]

Digital image processing (DIP) algorithms used in consumer electronics products have high computational complexities. Therefore, in this paper, we propose a novel low complexity 2D adaptive DIP algorithm. The proposed algorithm reduces computational complexities of 2D DIP algorithms by exploiting pixel correlations in input image without reducing quality of output image. We also designed a low energy 2D adaptive DIP hardware implementing the proposed algorithm. The proposed hardware is verified to work correctly on an FPGA board. It has significantly less energy consumption than original 2D DIP hardware. Therefore, it can be used especially in portable consumer electronics products. [ABSTRACT FROM AUTHOR]

In this paper, a novel frame rate up-conversion (FRUC) scheme to achieve better visual quality for highdefinition videos is proposed. The proposed algorithm has three main advantages over conventional FRUC algorithms. First, to increase the accuracy of motion estimation, this paper considers the diversity of motions, the retiming motion vectors of the previous motion field, and an adaptive update strategy. Second, the motion vector that is selected by using the sum of the absolute differences criterion is outputted after a geometric-based motion vector restriction, thereby improving the consistency of the motion vectors. Third, post-processing is performed on the estimated motion vectors based on localized global motions which are calculated by using motion histograms. Experimental results show that the performance of the proposed algorithm significantly outperforms that of traditional methods1. [ABSTRACT FROM PUBLISHER]

A new fast forward error correction (FEC) allocation algorithm for unequal error protection (UEP) of video transmission over wireless channels is proposed in this paper. First, an UEP scheme, which takes into consideration the non-uniformly distributed importance of frames in a group of pictures (GOP) and macroblocks in a video frame, is proposed. An enhanced video error propagation model, namely expected number of macroblocks error propagation (ENMEP) is also proposed in this paper to measure the amount of error propagation caused by transmission errors. Finally, by making use of our proposed ENMEP error propagation model, a fast FEC allocation algorithm for our proposed UEP scheme is also proposed. Simulation results demonstrate that our scheme outperforms the previous UEP scheme and the classical equal error protection (EEP) scheme. [ABSTRACT FROM AUTHOR]

The paper presents an adaptive dimming technique to reduce backlight power consumption and enhance image contrast for global backlight applications. The proposed adaptive dimming technique consists of two new algorithms: backlight dimming algorithm and contrast enhancement algorithm. The backlight-dimming algorithm obtains appropriate 0% to 50% backlight power reduction depending on characteristics of the image data. The contrast enhancement algorithm not only reduces the adverse effect of backlight power saving, but also improves 20.75%enhancement of image contrast ratio on the average. Numerous simulation results are used for illustration of the effectiveness and merits of the proposed adaptive dimming technique. Experimental results are conducted to show the performance and usefulness of the proposed technique on a 2.2-inch mobile phone liquid crystal display (LCD) made by thin-film-transistor (TFT) technology. [ABSTRACT FROM AUTHOR]

This paper aims to design an efficient mixed serial five-stage pipeline processing hardware architecture of deblocking filter (DBF) and sample adaptive offset (SAO) filter for high efficiency video coding decoder. The proposed hardware is designed to increase the throughput and reduce the number of clock cycles by processing the pixels in a stream of 4 \times 36 samples in which edge filters are applied vertically in a parallel fashion for processing of luma/chroma samples. Subsequently these filtered pixels are transposed and reprocessed through vertical filter for horizontal filtering in a pipeline fashion. Finally, the filtered block transposed back to the original orientation and forwarded to a three-stage pipeline SAO filter. The proposed architecture is implemented in field programmable gate array and application specific integrated circuit platform using 90-nm library. Experimental results illustrate that the proposed DBF and SAO architecture decreases the processing cycles (172) required for processing each 64 \times 64 or large coding unit compared with the state-of-the-art literature with the increase of gate count (593.32K) including memory. The results show that the throughput of the proposed filter can successfully decode ultrahigh definition video sequences at 200 frames/s at 341 MHz. [ABSTRACT FROM PUBLISHER]

Data compression is commonly used in NAND flash-based solid state drives (SSDs) to increase their storage performance and lifetime as it can reduce the amount of data written to and read from NAND flash memory. Software-based data compression reduces SSD performance significantly and, as such, hardware-based data compression designs are required. This paper studies the latest lossless data compression algorithm, i.e., the Lempel-Ziv (LZ)4 algorithm which is one of the fastest compression algorithms reported to date. A data compression FPGA prototype based on the LZ4 lossless compression algorithm is studied. The original LZ4 compression algorithm is modified for real-time hardware implementation. Two hardware architectures of the modified LZ4 algorithm (MLZ4) are proposed with both compressors and decompressors, which are implemented on an FPGA evaluation kit. The implementation results show that the proposed compressor architecture can achieve a high throughput of up to 1.92 Gb/s with a compression ratio of up to 2.05, which is higher than all previous LZ algorithm designs implemented on FPGAs. The compression device can be used in high-end SSDs to further increase their storage performance and lifetime. [ABSTRACT FROM PUBLISHER]

Unpredictable battery lifetime arising from multitasking can have a significant negative effect on availability for mobile devices. In practice, some applications are prioritized and required to remain in operation for certain duration. This paper suggests a battery lifetime guaranteeing scheme for prioritized applications in multitasking mobile systems. The proposed approach profiles and analyzes the battery usage pattern of each task dynamically, and preserves the energy budget for operation of prioritized tasks for a guaranteed time. In addition, this paper proposes an energyconstrained scheduler that limits the energy consumption of tasks while preserving scheduling patterns, which translates to the QoS. The suggested scheme is implemented in a commercial smartphone and evaluated. The evaluation showed that the proposed scheme successfully provides guaranteed operation time for prioritized tasks. [ABSTRACT FROM AUTHOR]

In this paper, we developed a golf position analysis system with an inertial sensor and swing motion analysis algorithm that can be used in golf courses. Specifically, we developed a band for both wrists that analyzes the golf swing of whoever is wearing it. By analyzing the movements of both the right and left wrists of the golfer, their golf swing can be judged more accurately, which can be used to advise the golfer regarding their golf swing. Experimental results show that this portable instrument along with its swing motion detection algorithm is a promising training tool for golfers. [ABSTRACT FROM AUTHOR]

Capturing image with defocused background by using a large aperture is a widely used technique in digital single-lens reflex (DSLR) camera photography. It is also desired to provide this function to smart phones. In this paper, a new algorithm is proposed to synthesize such an effect for a single portrait image. The foreground portrait is detected using a face prior based salient object detection algorithm. Then with an improved gradient domain guided image filter, the details in the foreground are enhanced while the background pixels are blurred. In this way, the background objects are defocused and thus the foreground objects are emphasized. The resultant image looks similar to image captured using a camera with a large aperture. The proposed algorithm can be adopted in smart phones, especially for the front cameras of smart phones. [ABSTRACT FROM AUTHOR]

To reduce frame memory usage in LCD overdrive, block truncation coding (BTC) is commonly used due to its efficient coding and low implementation cost. However, the inherent limitation of BTC causes severe perceptual artifacts and degrades overdrive performance. To solve this problem, we propose an adaptive multi-level BTC (AM-BTC) in this paper. The AM-BTC firstly overcomes the limitation by adaptively selecting 2-level or 4-level BTC according to the edge property of the coding block. Then, to reduce the bit rate of AM-BTC we improve the 2-level and 4- level BTCs by using only luminance bit-map to represent three color bit-maps. As shown in simulation results, the AM-BTC successfully reduces the frame memory usage to 1/6 and significantly improves coding performance (up to 3.779 dB) as compared with other algorithms. When the AM-BTC is applied to LCD overdrive, it also improves overdrive performance up to 3.390 dB as compared with other competitive methods in literature. [ABSTRACT FROM AUTHOR]

This paper points out some problems inherent in H.264/AVC intra frame rate control (RC) and presents several new algorithms to solve them. Three main algorithms are proposed in this paper. Multiple quantization parameters (QPs) determination algorithm based on the statistics of the deviation measure is proposed. Thus, relatively accurate QP estimation can be achieved since it takes the features of the current frame content into consideration. Two slice-based RC schemes are also proposed to stabilize the output bit rate. The scene change is detected with the complexity of adjacent frames based on deviation measure, which not only generates stable bit rate output but also improves the video quality. The combination of all the above algorithms improve the average peak signal-to-noise ratio (PSNR) by 0.74 dB while keeping the mismatch of the bit rate output less than 7.18% compared to the H.264/AVC reference model, JM12.0, under various sequences. [ABSTRACT FROM AUTHOR]

This paper proposes to obtain 3D modeling of object surface and to create a relit image in real-time. The proposed algorithm uses a single camera and synchronized stereo lights to capture the light field images by turning on and off the lights alternatively. The light field images from the controlled lighting approximate the reflectance models on object surfaces. The surface normal directions of object surface are modeled by the dichromatic reflectance model and Phong's shading geometry. The estimated normal map of object surface improves the rendering quality in image based relighting system. The proposed system is efficiently implemented in GPU-based programming, so it operates in real-time including 3D modeling and rendering. The proposed system is expected to be useful for video conference system, where the users can be immersed in video teleconference as they were in a virtual environment. [ABSTRACT FROM AUTHOR]

This paper proposes a wavelet packet-based noise reduction algorithm for national television system committee (NTSC) images, in which the characteristics of a composite video burst signal (CVBS) are utilized. Most of conventional noise reduction algorithms apply spatial or spatio-temporal filtering only to the luminance signal, noting that the human eye is less sensitive to color than to luminance. Such noise reduction algorithms do not consider the real- world situation where a TV signal is transmitted over a noisy channel and decoded at a receiver. In this paper, ii is assumed that an NTSVC signal is transmitted as a CVBS and corrupted with white Gaussian noise (WGN) by the channel. A CVBS has characteristics different from those of speech or image signals in a sense that encoded color information is modulated onto a high- frequency color subcarrier. The wavelet packet-based approach is suitable for noise reduction of the CVBS because decomposing a one-dimensional CVBS into eight subbands provides a chance to process each subband separately. In the proposed wavelet packet-based noise reduction algorithm, wavelet packet filtering is employed in subbands containing the color information whereas Wiener filtering is used in the other subbands. The separate treatment of each wavelet subband depending on the characteristics of CVBS leads to effective color and edge preserving noise reduction. The performance of the proposed method is validated by experiments with generated and corrupted CVBS images. Experimental results with various test images show that the proposed algorithm is effective in terms of the noise reduction efficiency and edge and color preservation. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for the suppression of Random- Valued Impulsive Noise from corrupted images. The proposed method is composed of an efficient noise detector and a pixel-restoration operator. The noise detector has been used to discriminate the uncorrupted pixels from the corrupted pixels. The noise- free intensity values of the corrupted pixels have been computed by using Triangle-Based Linear Interpolation and the values of tuning parameters of the proposed method have been optimized with Differential Evolution algorithm. Extensive simulation experiments indicate that the proposed method significantly outperforms all of the comparison methods mentioned in this paper. The success of the proposed method over comparison methods is due to its excellent detail preservation performance independent from the level of noise density. [ABSTRACT FROM AUTHOR]

Home energy management requires accurate information about the appliances’ consumption pattern. This information can help consumers save energy, control their usage by shifting their usage to off-peak hours and reduce their electricity costs. Non-intrusive load monitoring (NILM) in which the power consumption profile of appliances are extracted from the aggregated signal of a household, provides this information. For the NILM problem, machine learning approaches as the training-based solutions require large training datasets for an accurate disaggregation and the optimization-based approaches employs prior information about the characteristics of appliances. This paper proposes a novel event-based optimization algorithm. In its first stage, the prior information about appliances is extracted from the events of the consumption profiles of appliances by means of clustering. Then, a new event-based down-sampling method and transition filtering are designed for decreasing the computation time of optimization. At the last stage of the proposed algorithm, post-processing considering ON duration of appliances and varying states are proposed to increase the accuracy of the power profile reconstruction. The proposed approach was successfully tested for the low-frequency dataset of a house from the REDD. Numerical results show the advantages of the proposed algorithm, marked improvement over classification-based NILM considering small training dataset and its applicability in disaggregating the power consumption measured by the smart meter. [ABSTRACT FROM AUTHOR]

As one of the main threats to people’s health, especially for the elderly, falls have caused a large number of accidents. Detecting falls in time can minimize the severity of the injury and save lives. Therefore, designing fall detection algorithms to assist people’s daily life has been a hot research topic. In the last decade, different fall detection approaches based on wearable sensors have been proposed. However, since the hardware resources of wearable sensors are very limited, designing accurate but energy-efficient fall detection algorithms remains an open challenge. To deal with this, an accurate but low-cost fall detection algorithm is proposed in this paper. Particularly, a novel cascade and parallel method that efficiently employs the characteristics of human falls and the advanced modeling ability of the neural network is proposed. Also, a novel design of a lightweight convolutional neural network with self-attention is proposed to achieve the best recognition/numerical complexity tradeoff. The proposed method, namely CMFALL, is evaluated together with a multitude of state-of-the-art models on a large dataset, where it performs the best with an F1-score exceeding 99%. Meanwhile, its computational cost and model size are only a few thousandths of other models. Such low computational cost and small size not only enable to embed it in a wearable sensor but also make the system power requirements quite low, which can enhance the autonomy of the wearable fall detector. [ABSTRACT FROM AUTHOR]

Instead of the flatbed scanner which moves slowly as it scans, we propose in this paper a new design of a high-speed and low-power scanner with a stitching of multiple image capture. We divide the area to be scanned into four parts, capture each image and then stitch these into a whole. Our design uses the compact camera module (CCM) advantages of high integrity, white balance, advanced calibration, and auto exposure for color and luminance, all of which reduce the software post-processing time. To solve the light reflection problem we propose an interleaved light source compensation method. To reduce power consumption and prevent light reflection among the four scan areas, we scan the four images one by one, during which a single CCM is turned on while the others are turned off We use field of view (FOV) calculation to obtain the overlap area used by the stitching algorithms. [ABSTRACT FROM AUTHOR]

For real-time video encoder, low-complexity video encoding algorithms are required in many applications. This paper provides an early termination scheme to make the conventional binary block motion estimation algorithm significantly faster. The difference between the intensity of original frame and its filtered version is used as an input to something in this paper. With video codec, the proposed scheme shows improved visual quality while reducing complexity. Experimental results are provided to compare the performance of the proposed scheme with the conventional algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a Modified Stripe-RGBW (MS-RGBW) color filter structure to keep the same high resolution, and obtain a higher brightness in comparison with conventional RGB color filters. An image-processing engine is also designed to achieve sharp text image for thin-film-transistor (TFT) LCD with the MS-RGBW color filter. In MS-RGBW color filter structure, each pixel with three sub-pixels is the same area to that in the conventional RGB stripe color filter, and each row shifts two sub-pixels. The image-processing engine consists of two new.algorithms: RGB-RGBW mapping algorithm and sub-pixel rendering algorithm. The RGB-RGBW mapping algorithm obtains a new RGBW image data without distortion in hue and saturation. The sub-pixel rendering algorithm transfers RGBW data into a MS-RGBW color filter structure in order to achieve sharp text image. Numerous simulation results are provided to illustrate the merits and performance of the proposed techniques. The usefulness of the proposed techniques for mobile phone displays is exemplified by conducting several experimental results on a 2.2-inch TFT LCD. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a synchronization receiver for MIMO-OFDM based mobile broadcasting system. A MIMO-OFDM receiver with algorithms for tracking of residual frequency offset (RFO) and sampling frequency offset (SFO) is designed and simulated. The proposed synchronization and compensation schemes are applied to IEEE 802.16e WiMAX and its performance is investigated by computer simulations in terms of mean square error (MSE) and bit error rate (BER). The proposed RFO and SFO estimator has a fast convergence and a small residual degradation even for high speed mobile station. [ABSTRACT FROM AUTHOR]

This paper addresses a movement-aware vertical (MA V) handover algorithm between WLAN and Mobile WiMAX for seamless ubiquitous access. An MA V handover algorithm is proposed in this paper to exploit movement pattern for avoiding unnecessary handovers in the integrated WLAN and Mobile WiMAX networks. If a mobile station (MS) `s velocity is high and its movement pattern is irregular, unnecessary handovers likely occur more frequently. Therefore, the MS velocity and moving pattern are important factors for the handover decision procedure. To avoid unnecessary handovers, the MA V handover algorithm adjusts the dwell time adaptively and predicts the residual time in the cell of target base station (BS). Consequently, the adaptive dwell timer of MA V handover algorithm allows an MS a better connection as long as possible. Our simulation results show that the reduction of unnecessary handovers by leads to sign significant throughput improvements. [ABSTRACT FROM AUTHOR]

In this paper, an integrated music recommendation system is proposed, which contains the Junctions of automatic music genre classification, automatic music emotion classification, and music similarity query. A novel tempo feature, named as log-scale modulation frequency coefficients, is presented in this paper. With AdaBoost algorithm, the proposed tempo feature is combined with timbre features and improves the performance of music genre and emotion classification. Comparing with the conventional methods based on timbre features, the precision of five-genre classification is enhanced from 86.8% to 92.2% and the accuracy of four-emotion classification is increased from 86.0% to 90.5%. Based on the results of music genre/emotion classification, we design a similarity query scheme, which can speed up the similarity query process without decreasing the precision. Furthermore, all the features employed in this paper are extracted from the data of MP3 partially decoding, which significantly reduces the feature extraction time. [ABSTRACT FROM AUTHOR]

3D contents have been becoming one of attractive multimedia and reality. In computer vision, 2D-to-3D conversion techniques require estimating missing data from noisy observations. When there is no missing data in the observation matrix, the accurate solution of such problem is known to be given by Singular Value Decomposition (SVD). In the case of converting already recorded monoscopic video contents to 3D, several entries of the matrix have not been observed. Therefore, the problem has no simple solution, so it is necessary to estimate missing data. In this paper, we propose an estimation algorithm of missing data with minimizing the influence of noise embedded when tracking feature points from partial observations. The proposed method is an iterative affine SVD factorization method which can estimate the model parameters, given an incomplete set of the observation matrix. The main idea of our algorithm is to estimate missing data accurately even under noise distribution by using geometrical correlations between 2D and 3D error space. This paper consists of three main phases: geometrical correlations for estimating missing data, estimation algorithm, and analyzing the results for video sequences. The accurate results in practical situations as demonstrated here with synthetic and real video sequences show the efficiency and flexibility of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a novel contrast enhancement algorithm is proposed. The proposed approach enhances the contrast without losing the original histogram characteristics which is based on the Histogram Specification technique. It is expected to eliminate the annoying side effects effectively by using the differential information from the input histogram. The experimental results show that the proposed Dynamic Histogram Specification (DHS) algorithm not only keeps the original histogram shape features but also enhances the contrast effectively. Moreover, the DHS algorithm can be applied by simple hardware and processed in real-time system due to its simplicity. [ABSTRACT FROM AUTHOR]

In this paper, we present design and real-time implementation of a single-channel adaptive feedback active noise control (AFANC) headset for audio and communication applications. Several important design and implementation considerations, such as the ideal position of error microphone, training signal used, selection of adaptive algorithms and structures will be addressed in this paper. Real-time measurements and comparisons are also carried out with the latest commercial headset to evaluate its performance. In addition, several new extensions to the AFANC headset are described and evaluated. [ABSTRACT FROM AUTHOR]

Until recently, consumer electronics devices, PCs, and peripherals in home have been primarily confined to the links that allow consumers to access them with wired connections. Furthermore, there are increasing demands for wireless home entertainment network In order to satisfy consumers' demands for wireless home entertainment network in order to support low cost, reliable and wireless connections, we propose DS-UWB system using STBC with Rake receiver capable of resolving multipath components. The significant improvement is achieved in the proposed system. This paper evaluates the performance of the proposed system and examines the algorithms for improving reliability and performance of the proposed system. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new carrier frequency offset (CFO) estimation algorithm and a new CFO correction structure in the multi-stage synchronization strategy in time and frequency domain for OFDM The new CFO estimation algorithm uses all pilots including continual pilots (CP) and scattered pilots (SP) to estimate the CFO in frequency domain, and it can acquire more accurate estimation results than the conventional algorithm only using CP. The new CFO correction structure is a double-loop structure, and in the double-loop synchronization structure, "fractional" frequency offset (FFO) is corrected using a long loop as conventional method, however, "integral" frequency offset (IFO) does not go back to the time domain, and it is recovered using a short loop in frequency domain, which can shorten the convergence time of frequency synchronization. The analysis and simulations show the improved performance of the proposed CFO estimation algorithm and the double-loop correction structure. [ABSTRACT FROM AUTHOR]

In this paper, a motion compensated frame interpolation (MCI) algorithm adapting new block-based motion estimation (BME), which is overlapped block-based motion estimation (OBME), is proposed for frame rate up-conversion (FRC). Unlike conventional BME algorithms, where a video frame is divided into many non-overlapping square blocks of pixels, the proposed BME is executed using an overlapped matching block in order to get more accurate motion trajectory. To reduce computational complexity caused by the OBME, a sub-sampled pixel block is used for the OBME. The proposed OBME is executed with the various overlapped blocks that have different block sizes and sub-sampling ratios. In this paper, instead of mean absolute difference (MAD) used for general BME, a modified MAD is applied for the OBME. The MAD proposed is weighted using the magnitude of MV that corresponds to the estimating position. From the simulation results, the proposed methods show better performance in estimating "true motion" and reducing blocking artifacts with less complexity in calculation compared to a conventional method. [ABSTRACT FROM AUTHOR]

This paper presents a novel implementation of rank-order filtering using maskable memory. Based on a generic bit-sliced rank-order filtering algorithm the proposed design uses a special-defined memory, called parallel maskable memory (PMM) to realize major operations of rank- order filtering, threshold decomposition and polarization. In conventional designs, these operations are usually implemented as logic circuit and require complex computation. Using the memory-oriented architecture, the proposed rank-order filter can benefit from high flexibility, low cost and high speed PMM has features of bit-sliced read, partial write, and pipelined processing. Bit-sliced read and partial write are driven by maskable registers. The maskable registers allows PMM to configure operating bits for parallel read/write operations. Combining the bit-sliced read with polarization selector allows PMM to perform polar determination while the partial write achieves polarization. Recursively combining the bit-sliced read and partial write, PMM can effectively realizes rank-order filtering in terms of cost and speed. [ABSTRACT FROM AUTHOR]

The Motion estimator is a key element in many video compression systems and it tends to dominate the power consumption in them. With increasing demand of portable, power-aware multimedia devices, an architecture that can be flexible in both power consumption and compression quality is essential. To meet this requirement, this paper presents a novel power-aware architecture, called the Vario-Power Architecture, for the motion estimation. Based on a semi- systolic array with the content-based subsample algorithm, the architecture real-time disables some processing elements to reduce power consumption. By performing the edge extraction first, a threshold is then set as the criterion of whether to enable or disable processing elements and thus the switch activities of the system can be reduced As the simulation shows, the architecture may operate at different power consumption modes according to the remaining capacity of the battery pack giving little quality degradation and the power overhead under 0.36%. [ABSTRACT FROM AUTHOR]

Extensive researches have been conducted to enhance robustness for Internet video transmission. It has been found that feedback channel is an effective tool to provide error recovery ability and it is most suitable for interactive and conversational environments. Multiframe is another useful approach to enhance both coding efficiency and robustness. In this paper, we propose an algorithm which combines feedback channel and multiframe to achieve rapid error recovery ability for H.264 video. Simulation results show that our scheme can best utilize the feedback information. At the end of this paper, its application in conversational services such as Internet videophone is discussed. [ABSTRACT FROM AUTHOR]

As TV viewers inherently tend to avoid contents they might dislike, they do not provide equal amounts of positive and negative feedback on their viewing preferences. At the same time, mobile devices are becoming target platforms for multimedia content delivery. Personalized program guides need to cope with these challenges. They must not only properly recognize the undesired content, despite the lack of the learning data, but also provide valuable recommendations without compromising the user's privacy. Moreover, the complexity of the applied algorithms has to be low enough to match the limited hardware resources of the mobile terminals. In this paper, the design of such program guide is described. Several system architectures are developed and compared. The best performance is achieved for a single hidden layer autoencoder neural network trained with the FISTA algorithm1. [ABSTRACT FROM PUBLISHER]

In this paper, a vision based voice activity detection (VVAD) algorithm is proposed using chaos theory. In conventional VVAD algorithm, the movement measure of lip region is found by applying an optical flow algorithm to detect the visual speech frame using a motion based energy feature set. However, since motion based feature is unstable under illumination changes, a new form of robust feature set is desirable. It is propositioned that contextual changes such as lip opening or closing motion during speech utterances under illumination variation can be observed as chaos-like and the resultant complex fractal trajectories in phase space can be observed. The fractality is measured in phase space from two sequential video input frames and subsequently any visual speech frames are robustly detected. Representative experiments are performed in image sequence containing a driver scene undergoing illumination fluctuations in moving vehicle environment. Experimental results indicate that a substantial improvement is obtained in terms of achieving significantly lower false alarm rate over the conventional method. [ABSTRACT FROM PUBLISHER]

The design of continuous autofocus algorithms often involves repetitive, time-consuming field tests on real scenes. This paper presents a simulation method to expedite the design by replacing laborious field tests with simulation tests. The modeling of scene dynamics is achieved by decomposing a dynamic scene into a sequence of static scenes and representing the sharpness responses of the video camera to each static scene by a reciprocal focus profile. Three different scenes and the associated dynamic models are incorporated into the simulation framework to obtain effective clues for the refinement of continuous autofocus algorithms. Experimental results are provided to show the effectiveness of this design-by-simulation method. [ABSTRACT FROM AUTHOR]

Personal Video Recorders provide the facility of recording live broadcast streams thus users can replay their recordings whenever they want. However, during playback of those recorded streams, users are isolated from the live content (e.g., latest news,) in which they might be interested. In this paper, we propose an MPEG-2 Transport Stream compatible method which can inform the user about live content that's in user interest area during playback. The method-specific structures, algorithms and an implementation on a Linux platform are presented in the paper. [ABSTRACT FROM AUTHOR]

A smart device such as a television, tablet, and smartphone, often displays a compound image consisting of various types of sub-images, including texts and pictures. A text image displayed on a smart device is composed of red, green, and blue (RGB) sub-pixels having strong correlation among them. This paper proposes a new compression algorithm, called sub-pixel gradient compression (SPGC), that makes use of the correlation in a text in order to improve its compression efficiency. The initial step of the proposed algorithm converts a text into a de-colorized image in which RGB sub-pixels vary gradually. The de-colorization is a necessary step to further enhance the correlation among RGB sub-pixels, and thereby improving the compression efficiency. From the de-colorized text, the next step estimates the slopes of the gradual variations among sub-pixels and then encodes the slopes and their associated information as a bitstream. SPGC is a relatively simple algorithm because its main operation is the estimation of sub-pixel gradients and the precise estimation of the gradients makes it possible to reduce a degradation of the quality of the texts. Experimental results show that SPGC maintains lower complexity and a higher compression ratio than the compression standards including JPEG, JPEG-2000, H.264, or HEVC. [ABSTRACT FROM AUTHOR]

Flash memory has been a dominant storage medium in consumer electronics. Its wide deployment results from the remarkable progress in garbage collection mechanism which resolves the inherent limitation, not-in-place-update property, of flash memory. In this paper, we propose a new garbage collection management scheme, called selective-delay garbage collection, which can be used to optimize read operations. In our proposal, garbage collections are allowed to proceed only if they do not block the execution of incoming read operations. For this, the proposed scheme cooperates with an event queue in storage devices of consumer electronics. When read operations in the event queue are likely to collide with a garbage collection request, the read operations are processed preferentially by delaying garbage collection. This reduces the average read latency by avoiding time-consuming garbage collections. The experimental results with realistic workloads show that average read latency decreases by up to 13.53%, and the time elapsed by garbage collections is reduced by up to 78.37%, whereas the increase in write latency is limited to 0.83%. [ABSTRACT FROM PUBLISHER]

This paper presents a neural network-based method to generate multiple images with different exposures from a single input low dynamic range (LDR) image for improved high dynamic range (HDR) imaging. The proposed algorithm consists of three steps: 1) 2-D histogram estimation; 2) neural network-based LDR images estimation; and 3) generation of an optimal set of differently exposed images. The proposed method first generates image features by estimating a patched-based 2-D histogram. The extracted features are used in an input layer of the neural network, which plays a role to select an optimal set of LDR images. A set of LDR images is generated using a curvature-based contrast enhancement method. Experimental results show that the proposed method can generate an optimal set of LDR images using neural network and provide improved HDR images. In addition, the proposed method can be implemented as a preprocessing step in most existing HDR frameworks. The proposed HDR approach is considered as a single-input method that gives almost the same performance to multiple image-based HDR method. [ABSTRACT FROM PUBLISHER]

In this paper, we utilize a closed-set speaker-identification approach to convey the ratings needed for collaborative filtering-based recommendation. Instead of explicitly providing a rating for a given program, users use a speech interface to dictate the desired rating after watching a movie. Due to the inaccuracies that may be imposed by a state-of-the-art speaker identification system, it is possible to mistake a user for another user in the household, especially when the users exhibit similar or identical age and gender demographics. This leads to the undesirable effect of injecting unwanted ratings into the collaborative rating matrix, and when the users have different tastes, can result in the recommendation of undesirable items. We therefore propose a simple confidence-based heuristic that utilizes the log-likelihood scores from the speaker identification front-end. The algorithm limits the degree to which unwanted ratings negatively affect the integrity of the ratings information. Using real-speaker utterances over a range of age and gender demographics, we compare our approach against upper and lower-bound (nonspeaker-identification-based) baseline systems. Results show that by taking the confidence into account of users that we were able to improve upon the lower-bound that unconditionally accepts ratings by a relative 6.9%. [ABSTRACT FROM PUBLISHER]