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检索条件"任意字段=2012 IEEE Visual Communications and Image Processing, VCIP 2012"

共 124 条记录，以下是21-30 订阅

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SEQM: EDGE QUALITY ASSESSMENT BASED ON STRUCTURAL PIXEL MATCHING

SEQM: EDGE QUALITY ASSESSMENT BASED ON STRUCTURAL PIXEL MATC...

引用

ieee visual communications and image processing (vcip)

作者： Jang, Won-Dong Kim, Chang-Su Korea Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781467344050;9781467344067

A novel quality metric for binary edge maps, called the structural edge quality metric (SEQM), is proposed in this work. First, we define the matching cost between an edge pixel in a detected edge map and its candidate matching pixel in the ground-truth edge map. The matching cost includes a structural term, as well as a positional term, to measure the discrepancy between the local structures around the two pixels. Then, we determine the optimal matching pairs of pixels using the graph-cut optimization, in which a smoothness term is employed to take into account global edge structures in the matching. Finally, we sum up the matching costs of all edge pixels to determine the quality index of the detected edge map. Simulation results demonstrate that the proposed SEQM provides more faithful and reliable quality indices than conventional metrics.

关键词： image quality assessment edge quality assessment binary edge map structural similarity pixel matching

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AN ADAPTIVE COVARIANCE-BASED EDGE DIFFUSION image ENLARGEMENT METHOD

AN ADAPTIVE COVARIANCE-BASED EDGE DIFFUSION IMAGE ENLARGEMEN...

引用

ieee visual communications and image processing (vcip)

作者： Fan, Tao Zhao, Haiwu Wang, Guozhong Chen, Jianwen Xu, Feng Villasenor, John Shanghai Univ Sch Commun & Informat Engn Shanghai 200072 Peoples R China Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)9781467344050;9781467344067

We discuss image or video enlargement methods aimed at computationally constrained environments. Traditional enlargement algorithms such as linear or cubic interpolation have been applied in many applications. However the performance of these approaches is limited by artifacts such as blurring and jagged edges. More sophisticated iterative and learning-based algorithms have been proposed to address these issues, but they typically involve very high computational complexity. We present an adaptive covariance-based edge diffusion (ACED) image enlargement method that offers both good performance and low complexity. Different from other edge-directed interpolation algorithms, the proposed method uses combination of a novel edge-directed judgment which can choose different spread templates adaptively to estimate local covariance coefficients and edge diffusion to reduce artifacts. Experimental results show that the proposed method gives performs well both in terms of subjective quality as well as objective measures.

关键词： Video Enlarge Video processing Web TV Convergence

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A NOVEL NO-REFERENCE image QUALITY ASSESSMENT METRIC BASED ON STATISTICAL INDEPENDENCE

A NOVEL NO-REFERENCE IMAGE QUALITY ASSESSMENT METRIC BASED O...

引用

ieee visual communications and image processing (vcip)

作者： Chu, Ying Mou, Xuanqin Hong, Wei Ji, Zhen Xi An Jiao Tong Univ Sch Elect & Informat Engn Inst Image Proc & Pattern Recognit Xian 710049 Peoples R China Shenzhen Univ Texas Instruments DSPs Lab Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China

ISBN: (纸本)9781467344050;9781467344067

No-reference image quality assessment (NR IQA) has wide applicability to many problems. This paper focuses on the mechanism of divisive normalization transform (DNT) which simulates the behavior of visual cortex neurons to extract the independent components of natural images, analyzes the difference between the statistics of neighboring DNT coefficients of the images of a variety of distortion, and proposes a novel solution for NR IQA metric design. We demonstrate that measuring the statistical independence between neighboring DNT coefficients could provide features useful for quality assessment. The performance of the proposed method is quite satisfactory when it was tested on the popular LIVE, CSIQ and TID2008 databases. The experimental results are fairly competitive with the existing NR IQA metrics.

关键词： image quality assessment no-reference statistical independence divisive normalization transform support vector regression

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SEGMENTATION-BASED VIEW SYNTHESIS FOR THREE-DIMENSIONAL VIDEO

SEGMENTATION-BASED VIEW SYNTHESIS FOR THREE-DIMENSIONAL VIDE...

引用

ieee visual communications and image processing (vcip)

作者： Loghman, Maziar Kim, Joohee IIT Dept Elect & Comp Engn Chicago IL 60616 USA

ISBN: (纸本)9781467344050;9781467344067

This paper investigates the use of segmentation in view synthesis for three-dimensional video. View synthesis is the process of generating novel views of a scene, using a set of views as the reference. Recently, several techniques that use depth maps for rendering virtual views have been suggested. However, inaccuracy in depth maps causes annoying visual artifacts in depth-based view synthesis. This paper presents an efficient depth image-based rendering technique based on segmentation using multi-level thresholding. In the proposed algorithm, first all the images are segmented according to the depth and the pixels belonging to different objects are warped and blended independently. Based on multi-level thresholding, an algorithm for finding the ghost contour pixels is provided which simplifies the computations. A novel inpainting method for disocclusions has been introduced which uses the segmented images to find the associated background boundary pixels. The experimental results show that the proposed algorithm improves the PSNR of the synthesized views up to 0 : 6 8 dB for the multi-view video test sequences and eliminates the annoying visual artifacts.

关键词： 3-D video view synthesis depth image-based rendering segmentation inpainting

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A LOW-COMPLEXITY SCREEN COMPRESSION SCHEME

A LOW-COMPLEXITY SCREEN COMPRESSION SCHEME

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ieee visual communications and image processing (vcip)

作者： Pan, Zhaotai Shen, Huifeng Lu, Yan Yu, Nenghai Li, Shipeng Univ Sci & Technol China Hefei 230026 Peoples R China Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9781467344050;9781467344067

This paper presents a block-based low-complexity screen compression scheme. In this scheme, the input screen is split into non-overlapping blocks which are classified as pictorial blocks and textual blocks. We design a low-complexity yet efficient algorithm to compress the textual blocks. We use base colors plus escape pixels to represent and quantize the text pixels, and such quantization mechanism not only achieves high compression efficiency but also keeps low encoding/decoding complexity. We also propose the two-direction predictive index coding and hierarchical pattern coding technologies to utilize the local spatial correlation and the global pattern correlation for text pixels. In addition, to utilize the correlation between the luminance and chrominance channels, we propose a joint-channel index coding method to further improve the compression efficiency. The compression efficiency and complexity of the proposed method is evaluated against the popular image codecs JPEG/JPEG200 and PNG, a recent published screen compression scheme HJPC as well as the popular video codec H.264.

关键词： Screen compression low-complexity compression compound image compression

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OPTIMIZING JPEG QUANTIZATION TABLE FOR LOW BIT RATE MOBILE visual SEARCH

OPTIMIZING JPEG QUANTIZATION TABLE FOR LOW BIT RATE MOBILE V...

引用

ieee visual communications and image processing (vcip)

作者： Duan, Ling-Yu Liu, Xiangkai Chen, Jie Huang, Tiejun Gao, Wen Peking Univ Inst Digital Media Sch EE&CS Beijing 100871 Peoples R China

ISBN: (纸本)9781467344050

Smart phones is bringing about emerging potentials in mobile visual search. Extensive research efforts have been made in compact visual descriptors. However, directly extracting visual descriptors on a mobile device is computationally intensive and time consuming. Towards low bit rate visual search, we propose to deeply compress query images by learning a customized JPEG quantization table in the context of visual search. Distinct from traditional image compression, by incorporating pair-wise image matching precision into distortion measure, we optimize quantization table to seek a better trade-off between image compression rate and visual search performance. An evolutionary algorithm is employed to learn an optimal quantization table. Under MPEG CDVS evaluation framework, extensive evaluation has been done including image retrieval and pair-wise matching over 1 million database images. Experimental results have demonstrated that our optimized quantization table works much better than JPEG default one in terms of retrieval/matching performance vs. a set of different operating points. The proposed low bit rate solution may be easily deployed to smart phones without hardware support, as a useful complement to the ongoing MPEG CDVS standardization efforts.

关键词： Mobile visual search image compression Quantization table image matching image retrieval

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INTEGRATING STEREOSCOPIC image TRANSCODING WITH RETARGETING FOR MOBILE STREAMING

INTEGRATING STEREOSCOPIC IMAGE TRANSCODING WITH RETARGETING ...

引用

ieee visual communications and image processing (vcip)

作者： Liu, Yanwei Ci, Song Liu, Jinxia Ye, Yun Qi, Ying Chinese Acad Sci Inst Acoust Beijing Peoples R China Univ Nebraska Lincoln Omaha NE 68182 USA Zhejiang Wanli Univ Ningbo Peoples R China

ISBN: (纸本)9781467344050;9781467344067

With the progresses in 3D imaging technologies, mobile stereoscopic images are gradually popular since it can provide the anytime and anywhere 3D viewing effects. Due to the heterogeneous transmission environments and various screen sizes of mobile devices, the stereoscopic image transcoding and retargeting are two completely independent adaptation techniques for mobile 3D image streaming. These two processing operations both deal with the disparity estimation. In this work, we propose to integrate stereoscopic 3D image transcoding with retargeting for mobile streaming. The stereoscopic image transcoding and retargeting are coupled through a straightforward link that provides the pixel-based disparity map from the retargeting stage to guide the transcoding for saving some computations while keeping efficient bit allocation. Our experimental results clearly demonstrate the advantage of coupling the transcoding with retargeting in terms of faster transcoding and saliency-based bit allocation for low bit-rate mobile streaming.

关键词： stereoscopic retargeting stereoscopic 3D image transcoding mobile 3D image streaming

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A LOSSLESS COLOR image COMPRESSION METHOD BASED ON A NEW REVERSIBLE COLOR TRANSFORM

A LOSSLESS COLOR IMAGE COMPRESSION METHOD BASED ON A NEW REV...

引用

ieee visual communications and image processing (vcip)

作者： Kim, Seyun Cho, Nam Ik Seoul Natl Univ Dept Elect Engn & Comp Sci INMC Seoul 151744 South Korea

ISBN: (纸本)9781467344050

In many conventional lossless color image compression methods, the pixels or lines from each color component are interleaved, and then they are predicted and coded. Also, it has been reported that the reversible color transform (RCT) followed by a grayscale encoder gives higher coding gain than the independent compression of each channel does. In this paper, we propose a lossless color image compression method that concentrates on the efficient coding of chrominance channels with a new color transform and hierarchical coding of chrominance channel pixels. Specifically, we first transform an input image with R, G, and B color space into YCu C-v color space using the proposed RCT, which shows better decorrelation performance than the existing RCT. After the color transformation, the luminance channel Y is compressed by a conventional lossless image coder, such as JPEG-LS, CALIC, or JPEG2000 lossless. Unlike the luminance channel, the chrominance channels C-u and C-v are relatively smooth and have different statistical characteristic. Therefore, the chrominance channels are differently encoded based on a hierarchical decomposition and directional prediction. Finally, effective context modeling for prediction residuals is adopted. Experimental results show that the proposed method improves the compression performance by 40% over the conventional channel independent compression methods and 5% over the existing methods that exploit the channel correlation.

关键词： lossless color image compression reversible color transform lifting hierarchical coding

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CONTEXT-AWARE SINGLE image SUPER-RESOLUTION USING LOCALITY-CONSTRAINED GROUP SPARSE REPRESENTATION

CONTEXT-AWARE SINGLE IMAGE SUPER-RESOLUTION USING LOCALITY-C...

引用

ieee visual communications and image processing (vcip)

作者： Tsai, Chih-Yun Huang, De-An Yang, Min-Chun Kang, Li-Wei Wang, Yu-Chiang Frank Acad Sinica Res Ctr Informat Technol Innovat Taipei 115 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Math Taipei Taiwan Acad Sinica Inst Sci Informat Taipei Taiwan

ISBN: (纸本)9781467344050;9781467344067

We present a novel learning-based method for single image super-resolution (SR). Given a single input low-resolution (LR) image (and its image pyramid), we propose to learn context-specific image sparse representation, which aims at modeling the relationship between low and high-resolution image patch pairs of different context categories in terms of the learned dictionaries. To predict the SR image, we derive the context-specific sparse representation of each image patch in the LR input with additional locality and group sparsity constraints. While the locality constraint searches for the most similar image patches and uses the corresponding high-resolution outputs for SR, the group sparsity constraint allows us to utilize the information from most relevant context categories for predicting the final SR output. Experimental results show the proposed method is able to quantitatively and qualitatively achieve state-of-the-art performance.

关键词： Super-resolution sparse representation self-learning group Lasso data locality

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NEW BOUNDS ON image DENOISING: VIEWPOINT OF SPARSE REPRESENTATION AND NON-LOCAL AVERAGING

NEW BOUNDS ON IMAGE DENOISING: VIEWPOINT OF SPARSE REPRESENT...

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ieee visual communications and image processing (vcip)

作者： Feng, Jianzhou Song, Li Huo, Xiaoming Yang, Xiaokang Zhang, Wenjun Shanghai Digital Media Proc & Transmiss Key Lab Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781467344050;9781467344067

image denoising plays a fundamental role in many image processing applications. Utilizing sparse representation and non-local averaging together is such a successful framework that leads to considerable progress in denoising. Almost all the newly proposed denoising algorithms are built base on it, different in detailed implementation, and the denoising performance seems converging. What is the denoising bound of this framework turns into a key question. In this paper, we assume all the possible algorithms under the framework can be approximated by a fixed two steps denoising process with different parameters. Step one cluster geometric similar image patches into groups so that patches within each group could be sparse represented under the basis of the group. Step two use the atoms of the group basis and radiometric similar patches of each patch for non-local averaging. The parameters of the process are the cluster number, the atoms and the number of radiometric similar patches for estimating each patch. Finally, the bound is derived as the minimum denoising error of all the possible parameters. Comparing with previous bounds, the new one is image specific and more practical. Experiment results show that there still exists room to improve the denoising performance for natural images.

关键词： image specific bound affine bias model Fisher information matrix

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