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To correct an over-exposure within an image, the over-exposed region (OER) must first be detected. Detecting the OER accurately has a significant effect on the performance of the over-exposure correction. However, the results of conventional OER detection methods, which generally use the brightness and color information of each pixel, often deviate from the actual OER perceived by the human eye. To overcome this problem, in this paper, we propose a novel method for detecting the perceived OER more accurately. Based on the observation that recognizing the OER in an image is dependent on the saturation sensitivity of the human visual system (HVS), we detect the OER by thresholding the saturation value of each pixel. Here, a function of the proposed method, which is designed based on the results of a subjective evaluation on the saturation sensitivity of the HVS, adaptively determines the saturation threshold value using the color and the perceived brightness of each pixel. Experimental results demonstrate that the proposed method accurately detects the perceived OER, and furthermore, the over-exposure correction can be improved by adopting the proposed OER detection method.

In this paper, we present a novel depth sensation enhancement algorithm considering the behavior of human visual system (HVS) toward stereoscopic image displays. On the basis of the recent studies on the just noticeable depth difference (JNDD), which represents a threshold that a human can perceive the depth difference between objects, we modify the depth image such that neighboring objects in the depth image can have a depth value difference of at least the JNDD. This modification is modeled via an energy minimization framework using three energy terms defined as depth data preservation, depth-order preservation, and depth difference expansion. The depth data term enforces minimal changes in the depth image with an additional weighting function that controls the direction of depth changes. The depth-order term restricts the inversion of the local and global depth orders among objects, and the JNDD term leads to an increase in the depth differences between segments. Throughout subjective quality evaluation on a stereoscopic image display, it is demonstrated that the human depth sensation is effectively improved by the proposed algorithm.

The two-dimensional (2D) discrete Fourier transform (DFT) in the sliding window scenario has been successfully used for numerous applications requiring consecutive spectrum analysis of input signals. However, the results of conventional sliding DFT algorithms are potentially unstable because of the accumulated numerical errors caused by recursive strategy. In this letter, a stable 2D sliding fast Fourier transform (FFT) algorithm based on the vector radix (VR) 2 × 2 FFT is presented. In the VR-2 × 2 FFT algorithm, each 2D DFT bin is hierarchically decomposed into four sub-DFT bins until the size of the sub-DFT bins is reduced to 2 × 2; the output DFT bins are calculated using the linear combination of the sub-DFT bins. Because the sub-DFT bins for the overlapped input signals between the previous and current window are the same, the proposed algorithm reduces the computational complexity of the VR-2 × 2 FFT algorithm by reusing previously calculated sub-DFT bins in the sliding window scenario. Moreover, because the resultant DFT bins are identical to those of the VR-2 × 2 FFT algorithm, numerical errors do not arise; therefore, unconditional stability is guaranteed. Theoretical analysis shows that the proposed algorithm has the lowest computational requirements among the existing stable sliding DFT algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust people counting system based on fusing the depth and vision data. Conventional algorithms utilize the monoscopic or stereoscopic vision data to count people. However, these vision-based people counting methods often fail due to occasional illumination change and crowded environment. In the proposed algorithm, both the top-view vision and depth images are captured by a video-plus-depth camera mounted on the ceiling. The depth image is first processed by a morphological operator to alleviate depth artifacts such as the optical noise and lost data. Then the human object is extracted using a human model from the preprocessed depth image. Finally, the trajectory of the detected object is established by applying the bidirectional matching algorithm. Experimental results show that the proposed algorithm achieves over 98% accuracy in various testing environments. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new sharpness enhancement algorithm for stereo images. Although the stereo image and its applications are becoming increasingly prevalent, there has been very limited research on specialized image enhancement solutions for stereo images. Recently, a binocular just-noticeable-difference (BJND) model that describes the sensitivity of the human visual system to luminance changes in stereo images has been presented. We introduce a novel application of the BJND model for the sharpness enhancement of stereo images. To this end, an overenhancement problem in the sharpness enhancement of stereo images is newly addressed, and an efficient solution for reducing the overenhancement is proposed. The solution is found within an optimization framework with additional constraint terms to suppress the unnecessary increase in luminance values. In addition, the reliability of the BJND model is taken into account by estimating the accuracy of stereo matching. Experimental results demonstrate that the proposed algorithm can provide sharpness-enhanced stereo images without producing excessive distortion. [ABSTRACT FROM AUTHOR]

In this letter, we propose an improved histogram modification based reversible data hiding technique. In the proposed algorithm, unlike the conventional reversible techniques, a data embedding level is adaptively adjusted for each pixel with a consideration of the human visual system (HVS) characteristics. To this end, an edge and the just noticeable difference (JND) values are estimated for every pixel, and the estimated values are used to determine the embedding level. This pixel level adjustment can effectively reduce the distortion caused by data embedding. The experimental results and performance comparison with other reversible data hiding algorithms are presented to demonstrate the validity of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel postprocessing technique based on the theory of the projection onto convex sets (POCS) in order to reduce the blocking artifacts in digital high definition television (HDTV) images. By detecting and eliminating the undesired high-frequency components, mainly caused by blocking artifacts, we propose a new smoothness constraint set (SCS) and its projection operator in the DCT domain. In addition, we propose an improved quantization constraint set (QCS) using the correlation of DCT coefficients between adjacent blocks. In the proposed technique, the range of the QCS is efficiently reduced as close to the original DCT coefficient as possible to yield better performance of the projection onto the QCS. Computer simulation results indicate that the proposed schemes perform better than conventional algorithms. Furthermore, we introduce a fast implementation method of the proposed algorithm. The conventional POCS-based postprocessing techniques require the forward/inverse discrete cosine transform (DCT/IDCT) operations with a heavy computational burden. To reduce the computational complexity we introduce a fast implementation method of the proposed algorithm that does not perform DCT/IDCT operations. Estimates of computation savings vary between 41% and 64% depending on the task. [ABSTRACT FROM AUTHOR]

This paper presents a new image stitching algorithm for mobile multimedia devices. In general, the stitched image obtained by optimal seam finding can avoid the ghost effects but sometimes experience the unconformity of the image structure and color differences near the transition region between images. To solve these problems, the proposed algorithm adopts the seam carving/inserting operator and exploits an adaptive color blending algorithm. Experimental results show that the proposed algorithm can produce a stitched image without visible artifacts including the ghost effects, the unconformity of the structure, and the visible color differences. With respect to the visual quality of the stitched images, the proposed algorithm significantly outperforms simple conventional stitching algorithms and is comparable to the computationally demanding Poisson image editing algorithm1. [ABSTRACT FROM AUTHOR]

Various tone reproduction operators have been proposed to display high dynamic range images on low dynamic range (LDR) devices. The gradient domain operator is a good candidate due to its capability of reducing the dynamic range and avoiding common artifacts including halos and loss of image details. However the gradient domain operator requires high computational complexity and often introduces low-frequency artifacts such as reversal of contrast between distant image patches. In order to solve these problems we present a new gradient domain tone reproduction method which adopts an energy functional with two terms one for preserving global contrast and the other for enhancing image details. In the proposed method the LDR image is obtained by minimizing the proposed energy functional through a numerical method. Simulation results demonstrate that the proposed method can not only achieve the significantly reduced computational complexity but also exhibit better visual quality as compared with conventional algorithms. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we introduce an algorithm for object tracking in video sequences. In order to represent the object to be tracked, we propose a new spatial color histogram model which encodes both the color distribution and spatial information. Using this spatial color histogram model, a voting method based on the generalized Hough transform is employed to estimate the object location from frame to frame. The proposed voting based method, called the center voting method, requests every pixel near the previous object center to cast a vote for locating the new object center in the new frame. Once the location of the object is obtained, the back projection method is used to segment the object from the background. Experiment results show successful tracking of the object even when the object being tracked changes in size and shares similar color with the background. [Copyright &y& Elsevier]

Abstract: This paper presents a real-time implementation of Motion-JPEG2000 encoder using a fixed-point DSP chip. Among several modules in JPEG2000 encoder, the lifting algorithm for discrete wavelet transform (DWT) and the embedded block coding with optimized truncation (EBCOT) comprise more than 85% of the encoding complexity. Thus, it is very important to design and optimize these two modules in order to increase the performance of the hardware implementation. First we propose an overlapped block transferring (OBT) method that can significantly improve the performance of the lifting algorithm for DWT by increasing the cache hit rate. We show that the execution time of the lifting scheme can be further reduced by programming the DSP software using the single instruction multiple data (SIMD) instructions and the super scalar pipeline structure. Moreover, we introduce a parallel-pass method for fast implementation of EBCOT. This method reduces the processing time of EBCOT by processing the three coding passes of the same bit-plane in parallel. Experimental results show that our developed Motion-JPEG2000 DSP system meets the common requirement of the real-time video coding [30 frames/s (fps)] and is proven to be a practical and efficient DSP solution. [Copyright &y& Elsevier]