2012 Visual Communications and Image Processing最新文献_第7页

A study on efficient compression of multi-focus images for dense Light-Field reconstruction 密集光场重建中多聚焦图像的有效压缩研究

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410759

Takashi Sakamoto, K. Kodama, T. Hamamoto

{"title":"A study on efficient compression of multi-focus images for dense Light-Field reconstruction","authors":"Takashi Sakamoto, K. Kodama, T. Hamamoto","doi":"10.1109/VCIP.2012.6410759","DOIUrl":"https://doi.org/10.1109/VCIP.2012.6410759","url":null,"abstract":"Light-Field enables us to observe scenes from free viewpoints. However, it generally consists of 4-D enormous data, that are not suitable for storing or transmitting without effective compression. 4-D Light-Field is very redundant because essentially it includes just 3-D scene information. Actually, although robust 3-D scene estimation such as depth recovery from Light-Field is not so easy, a method of reconstructing Light-Field directly from 3-D information composed of multi-focus images without any scene estimation is successfully derived. Previously, based on the method, Light-Field compression via synthesized multi-focus images as effective representation of 3-D scenes was proposed. In this paper, we study efficient compression of multi-focus images synthesized from dense Light-Field by using DWT instead of DCT-based compression in order to suppress degradation such as block noise. Quality of reconstructed Light-Field is evaluated by PSNR and SSIM for analyzing characteristics of residuals. Experimental results reveal that our method is much superior to Light-Field compression using disparity-compensation at low bit-rate.","PeriodicalId":103073,"journal":{"name":"2012 Visual Communications and Image Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133835820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

A control-theoretic approach to rate adaptation for dynamic HTTP streaming 一种动态HTTP流速率自适应的控制理论方法

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410740

Chao Zhou, Xinggong Zhang, Longshe Huo, Zongming Guo

引用次数: 62

A novel no-reference image quality assessment metric based on statistical independence 一种基于统计独立性的无参考图像质量评价方法

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410790

Y. Chu, X. Mou, Wei Hong, Z. Ji

引用次数: 6

Robust wheelchair pedestrian detection using sparse representation 基于稀疏表示的鲁棒轮椅行人检测

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410801

Po-Jui Huang, Duan-Yu Chen

{"title":"Robust wheelchair pedestrian detection using sparse representation","authors":"Po-Jui Huang, Duan-Yu Chen","doi":"10.1109/VCIP.2012.6410801","DOIUrl":"https://doi.org/10.1109/VCIP.2012.6410801","url":null,"abstract":"Detecting pedestrians with disability in surveillance videos is practical for the implementation of automated alert/assistance technology. This paper presents a novel approach for the dimensionality reduction which employs sparse representation to improve the generalization capability of a classifier. To characterize pedestrian with disability, we create directional maps by determining the dominant direction of motion in each local spatiotemporal region using 3D orientation filters, and then uses the maps in real-time surveillance settings to detect pre-defined types. Mathematically, the derived algorithm regards the input features as the dictionary in sparse representation, and selects the features that minimize the residual output error iteratively, thus the resulting features have a direct correspondence to the performance requirements of the given problem. Furthermore, the proposed algorithm can be regarded as a sparse classifier, which selects discriminative features and classifies the training data simultaneously. Experimental results obtained using the extensive dataset show the superior performance of our method and thus demonstrate its robustness with the novel sparse representation-based disabled pedestrian detector.","PeriodicalId":103073,"journal":{"name":"2012 Visual Communications and Image Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130312882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Background modeling using Local Binary Patterns Of Motion Vector 使用运动矢量局部二进制模式进行背景建模

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410784

Tingting Wang, Jiuzhen Liang, Xiaolong Wang, Shizheng Wang

引用次数: 6

A hierarchical mode decision scheme for fast implementation of spatially scalable video coding 一种用于快速实现空间可扩展视频编码的分层模式决策方案

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410746

Xin Lu, G. Martin

引用次数: 3

Fast and reliable noise estimation algorithm based on statistical hypothesis tests 基于统计假设检验的快速可靠的噪声估计算法

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410754

Ping Jiang, Jianzhou Zhang

引用次数: 6

User-adaptive mobile video streaming 用户自适应移动视频流

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410862

Y. Reznik, E. Asbun, Z. Chen, Yan Ye, E. Zeira, R. Vanam, Zheng Yuan, Gregory Sternberg, A. Zeira, Naresh Soni

引用次数: 9

The hierarchical signal dependent transform: Creating orthonormal basis that match local signal characteristics 层次信号相关变换:创建匹配局部信号特征的标准正交基

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410820

Vanessa Testoni, M. H. M. Costa, Dinei Fiorendo

引用次数: 0

Layered compression for high dynamic range depth 分层压缩的高动态范围深度

2012 Visual Communications and Image Processing Pub Date : 2012-11-01 DOI: 10.1109/VCIP.2012.6410786

Dan Miao, Jingjing Fu, Yan Lu, Shipeng Li, Chang Wen Chen

{"title":"Layered compression for high dynamic range depth","authors":"Dan Miao, Jingjing Fu, Yan Lu, Shipeng Li, Chang Wen Chen","doi":"10.1109/VCIP.2012.6410786","DOIUrl":"https://doi.org/10.1109/VCIP.2012.6410786","url":null,"abstract":"With the rapid development of depth data acquisition technology, the high precision depth becomes much easier to access in real-time by depth sensors, and the generated high dynamic range (HDR) depth is widely adopted to benefit the depth assistant applications. Accordingly, the HDR depth compression becomes essential for the efficient depth storage and transmission. In this paper, we introduce a layered compression framework for HDR depth to achieve efficient and low-complexity depth compression. To leverage the state-of-art 8-bit image/video encoders, the HDR depth is partitioned into two layers: most significant bit (MSB) layer and least significant bit (LSB) layer. For MSB layer, an error controllable pixel domain encoding scheme is proposed to guarantee the compatibility for existing 8-bit codec by controlling quantization errors added back to LSB layer. Meanwhile, the efficient major color extraction and adaptive quantization enhance the coding performance of MSB layer. For LSB layer, the layer data with limited dynamic range is compressed by normal 8-bit image/video based encoding scheme. The experimental results demonstrate that our coding scheme can achieve real-time depth compression with the satisfactory reconstruction quality. The encoding time is less than 31ms/frame and the decoding time is around 20ms/frame in average. Our compression scheme can be easily integrated into the real-time depth transmission system.","PeriodicalId":103073,"journal":{"name":"2012 Visual Communications and Image Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121540710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1