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Wu J.,Shanghai University | Wang Y.,Key Laboratory of Advanced Display and System Application | Wang Y.,Shanghai University | Zhu K.,Shanghai University | Zhu Y.,Shanghai University
VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing | Year: 2016

Most traditional image coding schemes based on compressed sensing exploited the sparse domain in fixed bases and less consider the image non-stationary characteristic and human visual characteristic, which leads to poor performance of the reconstruction. In this paper, we proposed a novel sparse CS scheme combined with just-noticeable difference (JND) Model and random permutation. Firstly, the DCT-based JND profile has been utilized to remove the perceptual redundancies which also makes the signal sparser, then the random permutation is adopted to balance the sparsity of each block in image. Experimental results show that the proposed perceptual sparse algorithm outperforms some existing approaches, and it can achieve better subjective and objective image quality compared to other algorithms when the sampling rate is above 0.3. © 2016 IEEE.


Ma R.,Shanghai University | Ma R.,Key Laboratory of Advanced Display and System Application | Hu X.,Shanghai University | Hu X.,Key Laboratory of Advanced Display and System Application | And 6 more authors.
Communications in Computer and Information Science | Year: 2017

Multi-view video plus depth (MVD) is an efficient format of 3D video. MVD video can be encoded by either H.264/AVC or HEVC standard to gain higher compression ratio, which benefits their broadcasting over the Internet. However, the encoded and transferred MVD video tends to develop worse visual quality degradation caused by lossy network channel. Therefore, error concealment is here to help refrain this problem. In this paper, we propose a classification-related error concealment method for MVD video. Within our method, motion-based classification is used to judge whether the corrupted blocks are static or not. If so, the blocks from reference frames are adopted to conceal the corrupted blocks. Otherwise, view-specific based concealment procedures, which are designed in accordance with view features, are used to conceal the corrupted blocks in different views. Experimental results on AVC-based Test Model (ATM) show the superiority of this concealment scheme to several other error concealment methods in PSNR along with acceptable execution time increase. © Springer Nature Singapore Pte Ltd. 2017.


Yang C.,Shanghai University | An P.,Shanghai University | An P.,Key Laboratory of Advanced Display and System Application | Shen L.,Shanghai University | And 2 more authors.
Circuits, Systems, and Signal Processing | Year: 2017

In the multi-view video plus depth 3D video coding, texture image and depth map are coded jointly. The texture image is utilized for displaying and synthesizing the virtual view as reference image. The depth map provides the scene geometry information and is utilized to synthesize the virtual view at the terminal through Depth-Image Based Rendering technique. The distortion of the compressed texture image and depth map will be propagated to the synthesized virtual view. Besides the coding efficiency of texture image and depth map, bit allocation between texture image and depth map also has a great effect on the synthesized virtual view quality. Several methods are proposed for bit allocation between texture image and depth map, but most of them attempt to allocate a fixed target bitrate based on virtual view distortion model to achieve optimal synthesized virtual view quality, and the modeling process brings extra complexity. In practical application, the video sequence has different contents and fixed bit ratio cannot achieve optimal performance. In this paper, we propose an adaptive bit allocation algorithm for 3D video coding. First, we present a model to estimate the synthesized virtual view distortion, and then adjust the bit ratio between adjacent views and between texture image and depth map at Group of Picture level based on the virtual view quality fluctuation. We adjust the bit ratio to achieve the optimal virtual view quality for different video contents. Experimental results demonstrate that the proposed algorithm can optimally allocate bits to achieve optimal virtual view quality under different target bitrates and for different video contents, and the computational complexity of the proposed algorithm is extremely low. © 2016, Springer Science+Business Media New York.


Li H.,Key Laboratory of Advanced Display and System Application | Li H.,Shanghai University | An P.,Key Laboratory of Advanced Display and System Application | An P.,Shanghai University | And 2 more authors.
Optical Engineering | Year: 2014

Three-dimensional (3-D) video brings people strong visual perspective experience, but also introduces large data and complexity processing problems. The depth estimation algorithm is especially complex and it is an obstacle for real-time system implementation. Meanwhile, high-resolution depth maps are necessary to provide a good image quality on autostereoscopic displays which deliver stereo content without the need for 3-D glasses. This paper presents a hardware implementation of a full high-definition (HD) depth estimation system that is capable of processing full HD resolution images with a maximum processing speed of 125 fps and a disparity search range of 240 pixels. The proposed field-programmable gate array (FPGA)-based architecture implements a fusion strategy matching algorithm for efficiency design. The system performs with high efficiency and stability by using a full pipeline design, multiresolution processing, synchronizers which avoid clock domain crossing problems, efficient memory managem ent, etc. The implementation can be included in the video systems for live 3-D television applications and can be used as an independent hardware module in low-power integrated applications. © The Authors.


Shi R.,Shanghai University | Liu Z.,Shanghai University | Liu Z.,Key Laboratory of Advanced Display and System Application | Xue Y.,Shanghai University
ISPACS 2010 - 2010 International Symposium on Intelligent Signal Processing and Communication Systems, Proceedings | Year: 2010

Salient object segmentation is an important technique for many content based applications. This paper presents an unsupervised salient object segmentation method under the graph cut optimization framework. First, we exploit a kernel density estimation based saliency model to generate the saliency map, which provides the useful cues for object segmentation. Then we exploit the saliency map to adaptively define the region cost term, the boundary cost term and their balancing weight in the cost function, which is minimized using graph cut to obtain a binary segmentation of salient objects. Experimental results on a variety of images demonstrate the better segmentation performance of our approach. © 2010 IEEE.


Fu Y.,Shanghai University | Fu Y.,Key Laboratory of Advanced Display and System Application | Wang Y.,Shanghai University | Wang Y.,Key Laboratory of Advanced Display and System Application | And 2 more authors.
ICALIP 2010 - 2010 International Conference on Audio, Language and Image Processing, Proceedings | Year: 2010

Image and video coding in block-based image coding can cause blocking artifacts, which severely degrade visual quality in the compressed sequences. Loop deblocking filter method can reduce these artifacts and improve the video objective and subjective quality obviously. In this paper, we propose an efficient deblocking filtering method for multiview video coding, which considers the color bleeding distortion. Experimental results show that this proposed algorithm outperforms the traditional deblocking algorithm in terms of PSNR and subjective visual quality when QP value is relatively high. ©2010 IEEE.


Xue Y.,Shanghai University | Shi R.,Key Laboratory of Advanced Display and System Application | Liu Z.,Shanghai University
Optical Engineering | Year: 2011

This paper proposes a novel saliency model using multiple region-based features. The original image is initially segmented into a set of regions using the mean shift algorithm, and region merging is performed to obtain a moderate segmentation result. Then, three types of regional saliency measures are calculated using region-based features including local/global color difference, orientation difference, and spatial distribution, and they are integrated into an overall regional saliency measure for each region. Finally, the pixel-wise saliency map is generated by combining regional saliency measures with the distance-weighted color similarity between each pixel and each region. Experimental results demonstrate that our saliency model achieves an overall better saliency detection performance than previous saliency models, and the saliency maps generated using our model are more suitable for content-based applications such as salient object detection, content-aware image retargeting, and object-based image retrieval. © 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).


Hu Y.-L.,Shanghai University | Hu Y.-L.,Key Laboratory of Advanced Display and System Application | Zhou C.,Key Laboratory of Advanced Display and System Application
Journal of Shanghai University | Year: 2010

In this paper, the design and verification process of an automobile-engine-fan control system on chip (SoC) are introduced. The SoC system, SHU-MV08, reuses four new intellectual property (IP) cores and the design flow is accomplished with 0.35 μm chartered CMOS technology. Some special functions of IP cores, the detailed integration scheme of four IP cores, and the verification method of the entire SoC are presented. To settle the verification problems brought by analog IP cores, NanoSim based chip-level mixed-signal verification method is introduced. The verification time is greatly reduced and the first tape-out achieves success which proves the validity of our design. © 2010 Shanghai University and Springer-Verlag Berlin Heidelberg.


Shi R.,Shanghai University | Liu Z.,Shanghai University | Liu Z.,Key Laboratory of Advanced Display and System Application | Du H.,Shanghai University | And 2 more authors.
IEEE Signal Processing Letters | Year: 2012

Salient object detection is an important technique for many content-based applications, but it becomes a challenging work when handling the cluttered saliency maps, which cannot completely highlight salient object regions and cannot suppress background regions. In this letter, we propose a novel approach to detect salient object from saliency map without manually setting any parameters. Region diversity maximization is used as the objective function to direct the object detection, and the optimal window for locating the salient object is obtained using an efficient iterative search scheme. Experimental results on different saliency maps demonstrate the overall better detection performance and computational efficiency of our approach. © 2012 IEEE.


Liu Z.,Shanghai University | Liu Z.,Key Laboratory of Advanced Display and System Application | Xue Y.,Shanghai University | Shen L.,Shanghai University | And 3 more authors.
Proceedings - International Conference on Image Processing, ICIP | Year: 2010

This paper proposes a nonparametric saliency model based on kernel density estimation (KDE) mainly aiming at content-based applications such as salient object segmentation. A set of KDE models are constructed on the basis of regions segmented using the mean shift algorithm. For each pixel, a set of color likelihood measures to all KDE models are calculated, and then the color saliency and spatial saliency of each KDE model are evaluated based on its color distinctiveness and spatial distribution. The final saliency map is generated by combining saliency measures of KDE models and color likelihood measures of pixels. Experimental results demonstrate the better saliency detection performance of our saliency model. © 2010 IEEE.

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