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Wang Z.,CAS Shanghai Advanced Research Institute | Wang Z.,University of Chinese Academy of Sciences | Wang P.,CAS Shanghai Advanced Research Institute | Zhang H.,CAS Shanghai Advanced Research Institute | And 3 more authors.
IEICE Transactions on Information and Systems | Year: 2014

High Efficiency Video Coding (HEVC) is the latest video coding standard that is supported by JCT-VC. In this letter, an encoding algorithm for early termination of Coding Unit (CU) and Prediction Unit (PU) based on the texture direction is proposed for the HEVC intra prediction. Experimental results show that the proposed algorithm provides an average 40% total encoding time reduction with the negligible loss of rate-distortion. © 2014 The Institute of Electronics, Information and Communication Engineers. Source

Wang C.,East China Normal University | Shen M.,University of Konstanz | Shen M.,South China University of Technology | Yao C.,Third Security | Yao C.,Shanghai Key Laboratory of Digital Media Processing and Transmission
Journal of Visual Communication and Image Representation | Year: 2015

A blind/no-reference (NR) method is proposed in this paper for image quality assessment (IQA) of the images compressed in discrete cosine transform (DCT) domain. When an image is measured by structural similarity (SSIM), two variances, i.e. mean intensity and variance of the image, are used as features. However, the parameters of original copies are actually unavailable in NR applications; hence SSIM is not widely applicable. To extend SSIM in general cases, we apply Gaussian model to fit quantization noise in spatial domain, and directly estimate noise distribution from the compressed version. Benefit from this rearrangement, the revised SSIM does not require original image as the reference. Heavy compression always results in some zero-value DCT coefficients, which need to be compensated for more accurate parameter estimate. By studying the quantization process, a machine-learning based algorithm is proposed to estimate quantization noise taking image content into consideration. Compared with state-of-the-art algorithms, the proposed IQA is more heuristic and efficient. With some experimental results, we verify that the proposed algorithm (provided no reference image) achieves comparable efficacy to some full reference (FR) methods (provided the reference image), such as SSIM. © 2015 Elsevier Inc. All rights reserved. Source

Yang H.,Shanghai JiaoTong University | Yang H.,Shanghai Key Laboratory of Digital Media Processing and Transmission | Cao Y.,Shanghai JiaoTong University | Su H.,Shanghai JiaoTong University | And 2 more authors.
Multimedia Tools and Applications | Year: 2014

As a particular class of public security issues, the large-scale crowd analysis plays a very important role in video surveillance application. This paper proposes a sparse spatial-temporal local binary pattern (SST-LBP) descriptor to extract dynamic texture of the walking crowd which can be applied to the crowd density estimation and distribution analysis. The proposed approach consists of four steps. First of all, sparse selected locations are extracted, which vary notably in both spatial domain and temporal domain. Afterwards, we propose a SST-LBP algorithm to extract the local dynamic feature and utilize the local feature’s statistical property to describe the crowd feature. Thirdly, the overall crowd density level can be determined by classifying the crowd feature with support vector machine. Finally, the local feature is used to represent the local density and then the overall density distribution can be described. To improve the accuracy, we introduce the perspective correction into the detection of sparse selected locations and the spectrum analysis of SST-LBP code. The experiments on different datasets not only show that the proposed SST-LBP method is effective and robust on the large-scale crowd density estimation and distribution, but also indicate that the deformity correction is useful. Compared with other methods, the proposed method has the advantage of low computation complexity and high efficiency. In addition, it performs well on all density levels and can present local crowd distribution. © 2012, Springer Science+Business Media New York. Source

Han J.,Tongji University | Wang P.,Tongji University | Wang P.,Shanghai Key Laboratory of Digital Media Processing and Transmission | Liu F.,Tongji University | Zhu Y.,Tongji University
Journal of Communications | Year: 2011

This paper studies power allocation in coordinated multi-point (CoMP) transmission of 3GPP LTE-Advanced system with remote radio units(RRUs) power constraints. We apply block diagonal (BD) precoding to downlink transmission, and assume perfect knowledge of downlink channels and transmit messages at each transmit point. We propose a modified water-filling power (MWF) allocation algorithm in order to maximize the downlink sum capacity, at the same time the low complexity is achieved. The interior-point method is also used to solve the optimization problem. Simulations show that interior-point method converges after only a few iterative steps and the system capacity is near-optimal. As for complexity and power efficiency, MWF achieves a good compromise. © 2011 ACADEMY PUBLISHER. Source

Wang C.,East China Normal University | Shen M.,South China University of Technology | Yao C.,Third Security | Yao C.,Shanghai Key Laboratory of Digital Media Processing and Transmission
Multimedia Tools and Applications | Year: 2016

Dynamic weather conditions, such as rain and snow, often produce strong intensity discontinuity among frames, thus seriously degrade their visual or compression performance. How to remove these artifacts is a challenging task and has been intensively studies recently. The state-of-the-art algorithms detect these scratches before removing them from the scene. Visual effect of rain or snow is complex and difficult to be distinguished from the background; hence the precision of its detection and segmentation by hard decision is usually unsatisfactory. As an anisotropic filter performs well in structural noise removal, such as linear, planar as well as isotropic noise, it is utilized in this paper to analyze image content and suppress scratch noise simultaneously. Compared with the state-of-the-art algorithms, the proposed algorithm is better and more robust in dynamic scenes. © 2016 Springer Science+Business Media New York Source

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