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Efficient representation and coding of fine-granular motion information is one of the key research areas for exploiting inter-frame correlation in video coding. Representative techniques towards this direction are affine motion compensation (AMC), decoder-side motion vector refinement (DMVR), and subblock-based temporal motion vector prediction (SbTMVP). Fine-granular motion information is derived at subblock level for all the three coding tools. In addition, the obtained inter prediction can be further refined by two optical flow-based coding tools, the bi-directional optical flow (BDOF) for bi-directional inter prediction and the prediction refinement with optical flow (PROF) exclusively used in combination with AMC. The aforementioned five coding tools have been extensively studied and finally adopted in the Versatile Video Coding (VVC) standard. This paper presents technical details of each tool and highlights the design elements with the consideration of typical hardware implementations. Following the common test conditions defined by Joint Video Experts Team (JVET) for the development of VVC, 5.7% bitrate reduction on average is achieved by the five tools. For test sequences characterized by large and complex motion, up to 13.4% bitrate reduction is observed. Additionally, visual quality improvement is demonstrated and analyzed.

In this brief, Redundant Binary Representation (RBR) is applied in Montgomery modular multiplication (MMM) to eliminate the long carry chain and realize parallel computation. A novel MMM algorithm based on RBR is proposed. Based on the proposed algorithm, different sizes of high-performance and low-cost Montgomery multipliers are implemented in TSMC CMOS process technology. The experimental results demonstrate that our design has significant advantages in terms of performance, area and Area-Time-Product over previous researches. It’s worth mentioning that our 8192-bit Montgomery multiplier (TMSC 65nm) with 603MHz working frequency and 878.1K equivalent gates can complete the MMM in only 3403ns.

This paper describes a joint response to the Call for Proposals by Samsung, Huawei, GoPro, and HiSilicon on Video Compression with Capability beyond HEVC/H.265, jointly issued by ITU-T SG16 Q.6 (VCEG) and ISO/IEC JTC1/SC29/WG11 (MPEG). In the proposed codec, the coding framework supports hierarchical splitting with binary and ternary trees and flexible coding order representations. Additionally, novel compression tools on inter/intra prediction, in-loop filtering, and entropy coding have been proposed. The proposed compression scheme provides significantly higher compression capability than the state-of-the-art HEVC/H.265 standard for SDR (Standard Dynamic Range) category while maintaining complexity acceptable for emerging applications. When all the proposed algorithmic tools are used, the proposed video codec achieves approximately 40% bit-saving for the SDR cetegory on average compared to HEVC/H.265 anchor.

Due to the extensive development of fractures and serious heterogeneity in fractured reservoirs, it is difficult for the traditional numerical simulation method to invert its geology, which greatly limits the efficiency and accuracy of simulation and cannot realize the real-time optimization of production scheme. The connectivity model can only consider the two characteristic parameters of conductivity and connectivity volume, which does not involve complex and rigorous geological modeling. It can quickly and accurately reflect the state of the real reservoir, greatly reducing the simulation time, and is suitable for real-time production performance prediction of the reservoir. Due to the large difference in conductivity of fractured reservoirs, the difficulty of fitting increases. In this paper, the connectivity model is first applied to fractured reservoirs to realize the production dynamic simulation of fractured reservoirs. The optimization principle is used to optimize the injection-production scheme with the economic net present value as the objective function. In order to verify the method, the connectivity model is applied to Mu 30 of Changqing Oilfield in this paper. The results show that this method can effectively reflect the real production situation of the oilfield and the connectivity of the reservoir, and the simulation time is relatively fast. After optimization, the cumulative oil production of the reservoir increases by 8.1%, the cumulative water injection decreases by 2.3%, and the rising rate of water cut decreases by 58.8%, indicating that the connectivity model can realize the real-time production optimization of the reservoir.

Image compression has always been an important topic in the last decades due to the explosive increase of images. The popular image compression formats are based on different transforms which convert images from the spatial domain into compact frequency domain to remove the spatial correlation. In this paper, we focus on the exploration of data-driven transform, Karhunen-Loéve transform (KLT), the kernels of which are derived from specific images via Principal Component Analysis (PCA), and design a high efficient KLT based image compression algorithm with variable transform sizes. To explore the optimal compression performance, the multiple transform sizes and categories are utilized and determined adaptively according to their rate-distortion (RD) costs. Moreover, comprehensive analyses on the transform coefficients are provided and a band-adaptive quantization scheme is proposed based on the coefficient RD performance. Extensive experiments are performed on several class-specific images as well as general images, and the proposed method achieves significant coding gain over the popular image compression standards including JPEG, JPEG 2000, and the state-of-the-art dictionary learning based methods.

Recently, convolutional neural network (CNN)-based methods have achieved remarkable progress in image and video super-resolution, which inspires research on down-/up-sampling-based image and video coding using CNN. Instead of hand-crafted filters for up-sampling, trained CNN models are believed to be more capable of improving image quality, thus leading to coding gain. However, previous studies either concentrated on intra-frame coding or performed down- and up-sampling of entire frame. In this paper, we introduce block-level down- and up-sampling into inter-frame coding with the help of CNN. Specifically, each block in the P or B frame can either be compressed at the original resolution or down-sampled and compressed at low resolution and then, up-sampled by the trained CNN models. Such block-level adaptivity is flexible to cope with the spatially variant texture and motion characteristics. We further investigate how to enhance the capability of CNN-based up-sampling by utilizing reference frames and study how to train the CNN models by using encoded video sequences. We implement the proposed scheme onto the high efficiency video coding (HEVC) reference software and perform a comprehensive set of experiments to evaluate our methods. The experimental results show that our scheme achieves superior performance to the HEVC anchor, especially at low bit rates, leading to an average 3.8%, 2.6%, and 3.5% BD-rate reduction on the HEVC common test sequences under random-access, low-delay B, and low-delay P configurations, respectively. When tested on high-definition and ultrahigh-definition sequences, the average BD-rate exceeds 5%.

To address the problem of poor applicability of the existing generative adversarial network (GAN) evaluation system, this paper introduces the remote sensing image information quantity calculation system into the generative adversarial network evaluation indicator system, proposes an end-to-end GAN evaluation method based on the single-pixel image information quantity indicator, and uses EDS, ENDS, and InfoDS to evaluate the stability of the generator training process, mode collapse, diversity generation, and training failure problem is effectively monitored, which independent of loss function, learning rate.

In order to improve the chaotic encryption ability of color images, a chaotic encryption technology of color images based on improved neural network and chaotic random nonlinear feature mapping is proposed. The multi-pass filter detector is used to collect the feature information of color images, multi-dimensional phase space hierarchical fusion and feature evolution clustering analysis are carried out on the collected color images, the deep chaotic encryption method is used to realize the arithmetic mapping coding processing of color images, the random nonlinear mapping encryption chaotic key control scheduling model of color images is constructed, and the chaotic mapping coding sequence distribution diagram of color image chaotic encryption is established by combining the segmentation prior knowledge of multi-dimensional multi-view images. The shallow feature information and deep feature information of color image are analyzed, and the improved convolutional neural network technology is used to realize information fusion of feature information of each layer, and the chaotic encryption and recognition optimization of color image is realized by using the chaotic map coding sequence distribution map fusion algorithm. Simulation results show that this method has higher accuracy and lower error rate in chaotic encryption of color images, and improves the ability of color image recognition and detection.

The existing data mining methods for suspicious electricity stealing detection, as utilized based on multi-month power consumption data, are of low timeliness. In this light, this paper proposes an online method for suspicious electricity stealing analysis, which is based on level change detection (LCD) on the users' daily power consumption sequence. The power consumption data are turned into cumulative sum values so as to reduce the influence of short-time data abnormality on the detection results. In the case study section, a numerical example is offered based on the daily consumption data of the customers in a residential area in North Shanghai, where the LCD method is also compared with other detection methods. The results show that the LCD method is of high coverage and accuracy, meanwhile it can realize timely online detection by moving the data window.

When an unbalanced voltage drop occurs in the grid system , output power of distributed photovoltaic grid-connected system will generate second harmonics. In order to suppress the second harmonic, a new low voltage ride-through control strategy is proposed, which can adjust the harmonic suppression target according to the degree of voltage drop. This strategy can suppress the second harmonic of active power when the voltage drop is low, and suppress the second harmonic of reactive power when the voltage drop is large. The control strategy is simulated in MATLAB, and the results testified its effectiveness.

this paper presents a novel power flow method based on the Modified Backward-Forward Sweep algorithm of radial Ship's Shore Power Supplying Networks without involving node number and special rules. This method makes full use of the structure characteristics of the radiation distribution network; through the establishment of loop chain and a directional node table, by using breadth-first to search node sequence of generated power flow calculation, using the linear trend equation iteration to get each node voltage, it does not require complex number of nodes and branch, does not need to form the node admittance matrix and triangular matrix, with simple input data format, rapid computing speed, less memory and good convergence. Finally, the model of power distribution system should be set up on MATLAB platform and realized by fast plural matrix operation function, a practical calculation example proved the effectiveness of the proposed algorithm.

In recent years, wavelet transform theory has been paid more and more attention in image fusion. With the development of wavelet transform image fusion, wavelet transform is introduced, and the basic principles and types of wavelet transform are introduced. Then, aiming at two images with different focal lengths, the discrete wavelet transform method of three-layer decomposition is used, the low-frequency and high-frequency components are fused by different fusion rules, and the differences of different fusion strategies in wavelet transform image fusion are compared and analyzed. Experimental results show that wavelet transform has the characteristics of convenient application, rapid fusion and real image, and has a good application prospect.

This paper proposes a novel video compression scheme for high-quality video service and emerging applications such as 360-degree omnidirectional and high dynamic range video coding. The coding framework supports hierarchical splitting of blocks with binary and ternary-split trees and flexible coding order representations. Moreover, minimal tool set to obtain high precision prediction and compression enhancement has been proposed. Compared to HEVC, bit-rate reduction of around 40% based on objective measures has been shown. This was one of the responses to the Call for Proposals (CfP) for VVC standardization.

The 360-degree video compression has two main challenges due to projection distortions namely the geometry distortion and the face boundary discontinuity. There are some trade-offs between selecting Equi-rectangular and polyhedron projections. In the Equi-rectangular projection, the geometry distortion is severer than the face boundary discontinuity, while for the polyhedron projections the face boundary discontinuity is severer than the geometry distortion. These two distortions will have side effects on the motion compensation and undermine the compression efficiency of the 360-degree video. In this paper, an integrated framework is developed to handle these two problems to improve the coding efficiency. The proposed framework mainly has two key contributions. First, we derive a unified advanced spherical motion model to handle the geometry distortion of different projection formats for the 360-degree video. When fitting the projection between the various projection formats and the sphere into the unified framework, a specific solution can be obtained for each projection format. Second, we propose a local 3-D padding method to handle the face boundary discontinuity between the neighboring faces in various projection formats of the 360-degree video. The local 3-D padding method can be applied to different projection formats through setting different angles between neighboring faces. These two methods are independent of each other and can also be combined into an integrated framework to achieve a better rate-distortion performance. The proposed framework can be seamlessly integrated into the latest video coding standard High Efficiency Video Coding. The experimental results demonstrate introducing proposed coding tools can achieve significant bitrate savings compared with the current state-of-the-art method.

With the large number of PV access in the medium and low voltage distribution network, the power quality problem of distribution network is becoming increasingly prominent. Therefore, it is necessary to test the power quality of distribution network with PV access and observe its power quality periodically. Based on this, this paper introduces the current commonly used power quality analyzer, and mainly describes the application steps and points for attention of HIOKIPW3198 power quality analyzer. Finally, this paper takes Shanghai Xinsheng semiconductor photovoltaic power generation system for an example, using HIOKIPW3198 power quality analyzer to test power quality on its workshop and 1# transformer low voltage side. Through the test and analysis, it is found that the voltage imbalance and frequency deviation of the company are within the allowable range, but there are slight voltage harmonic problems and serious current harmonic problems. The suggestion is that some measures should be taken to solve the problem. Otherwise, the power supply safety and quality of the company will be affected.

They were studied mainly that improving the power exporting capability of large-scale power grid with intensive electricity and the quality of power grid planning, on the premise of ensuring the security of power system. In view of the problems faced in planning and operation periods of such power grid, 3 kinds of sending power grid structure schemes were proposed, including single point AC interconnection, multipoint AC interconnection and single point AC with the addition of DC back-to-back interconnection between the newly-built higher voltage power grid and the existing power grid. The differences of the proposed structures were discussed including technical characteristics, power delivery capability, economy and so on. Then, it was clarified that the influence on improving the power transmission capacity of power grid of the connecting mode. It was shown that the number of connection points should be considered based on the demand and constraints of power transmission in different developing stages. Finally, the case study was carried out on some ultra-high voltage power grid planning.

The existing embedded routing technology has disadvantages of high price and high energy consumption. This paper studies an embedded router network with low power consumption and low price and supports network wireless access. Using NDN technology and embedded routers, through the combination of hardware and software, the embedded router network is built under the Linux platform to test and study the network performance. The results show that the embedded NDN-based router network has a strong flexibility. The advantages of simulation are high, and the function, reliability, cost, volume and other requirements of the application system are solved.

This letter proposes a new distributed Luby transform (LT) code which is particularly suitable for the multiple-access relay network with erasure channels. We analyze the asymptotic performance of our distributed coding scheme by virtue of AND-OR tree analysis and present the simulation results of finite length comparing with existing methodologies. The proposed coding scheme is shown to be superior to conventional strategies in presence of both source-relay and relay-sink erasures.

The polyhedron projection for 360-degree video is becoming more and more popular since it can lead to much less geometry distortion compared with the equirectangular projection. However, in the polyhedron projection, we can observe very obvious texture discontinuity in the area near the face boundary. Such a texture discontinuity may lead to serious quality degradation when motion compensation crosses the discontinuous face boundary. To solve this problem, in this paper, we first propose to fill the corresponding neighboring faces in the suitable positions as the extension of the current face to keep approximated texture continuity. Then a co-projection-plane based 3-D padding method is proposed to project the reference pixels in the neighboring face to the current face to guarantee exact texture continuity. Under the proposed scheme, the reference pixel is always projected to the same plane with the current pixel when performing motion compensation so that the texture discontinuity problem can be solved. The proposed scheme is implemented in the reference software of High Efficiency Video Coding. Compared with the existing method, the proposed algorithm can significantly improve the rate-distortion performance. The experimental results obviously demonstrate that the texture discontinuity in the face boundary can be well handled by the proposed algorithm., Comment: 6 pages, 9 figures

In order to study the novel biometric of eyebrow,,this paper presents an Eyebrows identity authentication based on wavelet transform and support vector machines. The features of the eyebrows image are extracted by wavelet transform, and then classifies them based on SVM. Verification results of the experiment on an eyebrow database taken from 100 of self-built personal demonstrate the effectiveness of the system. The system has a lower FAR 0.22%and FRR 28% Therefore, eyebrow recongnition may possibly apply to personal identification.

A real-time scene cut detection algorithm is proposed which shares the results of motion estimation with the video encoder.To deal with different kinds of scene cuts,two metric functions are introduced based on the statistics of the first and second order difference between the original pictures and their motion compensated pictures.The detection thresholds for each metric are adaptively adjusted according to the scenes.The experimental results and analysis show that the recall and precision of the proposed algorithm are generally higher than other tested ones at the cost of little computation time increment.

With the exponential growth of surveillance videos, conference videos and sports videos, videos with static cameras present an unprecedented challenge for high-efficiency video coding technology. The existing schemes developed for these videos mostly encode the background as the long-term reference (LTR) to further improve the coding efficiency. However, since the bit allocation of the long-term background reference is not intensively studied, the coding efficiency is still unsatisfactory. Based on the stability analysis of the video content, an efficient background picture coding algorithm for videos obtained from static cameras, which is embedded with the basic unit level bit allocation, is proposed in this paper. Experimental results reveal that on top of the default mode in HEVC, our method offers the performance with 10.8% BD-rate reduction on average. Compared with the state-of-the-art algorithm, it still outperforms for kinds of test sequences with negligible increases of computational complexity in both encoder and decoder.

The High Efficiency Video Coding (HEVC) utilizes Z-scan order to process coding units (CUs). For intra prediction, this order cannot fully exploit the spatial correlation between adjacent CUs. After transform and quantization, the residue still contains lots of energy along edges which consumes many bits for compression. To effectively reduce the residue energy along edges, a novel intra prediction approach is proposed, where the CU processing order is changed adaptively. Two additional orders are introduced in this paper besides traditional Z-scan order. Up to 1.9% bit saving is achieved in our experiments on HEVC test model. We also propose two fast order selection algorithms and the observed gains are obtained with 27% and 2% encoding time increase compared to HEVC, respectively.

Non-camera captured images (also known as compound image) contain a mixture of camera-captured natural images and computer-generated graphics and texts. Nowadays, there are more and more applications calling for non-camera captured image/video compression scheme. However, current video coding standards, which are designed for natural video, treat non-camera captured video less carefully. For example, the state-of-the-art video coding standard High Efficiency Video Coding (HEVC) may blur or even remove edges in text/graphic region. A lot of schemes are proposed to preserve direction property of texts and graphics, such as palette-based intra coding. In this paper, a novel palette coding scheme is proposed for palette-based intra coding in HEVC. The palette in a block is predicted from an adaptive palette template, which records the statistical non-local spatial correlation of an image. Every block chooses its own palette using the palette template as the prediction in a rate-distortion optimized manner. Experimental results show that the proposed scheme can achieve up to 5.2% bit-rate saving compared to the state-of-the-art palette-based coding scheme in HEVC.

Scalable video coding (SVC), which is an extension of H.264/AVC video coding standard, was introduced to provide scalability in different dimensions for adaptation to heterogeneous network and terminals. After the finalization of the new video coding standard called High Efficiency Video Coding (HEVC), the effort of the standardization committee has been redirected to the investigation of the scalable extension of HEVC. In addition to the basic inter-layer texture prediction mechanism, several other coding tools were proposed for coding performance improvement. Among those coding tools, the one called generalized residual prediction (GRP) scheme achieves most significant coding gain while the consumption of computational power is also huge. In this paper, the GRP mechanism is formulated and analyzed in detail. In addition, the combination of GRP mechanism with merge mode in HEVC is proposed for simplification of the existing GRP mechanism. Results show a better trade-off could be achieved by greatly reducing computational complexity while maintaining most of the coding gain.

Motion information occupies a considerable portion of the bit stream generated by the state-of-the-art video codecs. As a sequence, reducing bits on motion information can improve the overall performance of video compression. Various competition based motion vector coding (MVC) schemes were proposed for this goal. In this paper we propose a region based motion vector prediction (RMVP) algorithm to save signaling bits in conventional MVC schemes. Specifically, the motion vector predictor selection information is embedded into the parity of the motion vector differences which would be transmitted into the decoder. To obtain the modulated motion vector differences, the encoder needs to divide the reference frame into several regions and then perform constrained motion estimation in some of the regions. To confirm the advantages of RMVP over different MVC schemes, we implemented it on both KTA Software and TMuC test model. Experimental results show that RMVP outperforms existing MVC schemes.

This article proposes a model-free adaptive controller (MFAC) for BUCK converter by date-driven. It uses the model-free adaptive control algorithm based on the tight format linear method; this method has achieved an intelligent reasoning of the algorithm, and has rapid convergence for nonlinear controlled objects, so it restrains the time-varying parameters, the model mismatch and un-modeled dynamics effectively. Comparing and analyzing the simulated waveforms with the method of optimal control of buck converter by state feedback linearization, we can find that this method is simple and it avoids some complex steps such as building a precise mathematical model, and distinguishing CCM and DCM. Because the duty cycle makes the response more effective and rapid, the inductance electric current is steady. The analysis and simulation tests show good functions of the model-free adaptive control.