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CORC

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Data Compression and Parallel Computation Model Research under Big Data Environment 会议论文
作者:  Sun, Yueqiu;  Gong, Xian;  Yang, Yihe
收藏  |  浏览/下载：4/0  |  提交时间：2019/08/22
effective retransmission in network coding for tcp 期刊论文
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2011, 卷号: 6, 期号: 1, 页码: 53-62
Chen J.; Liu L. X.; Hu X. H.; Tan W.
收藏  |  浏览/下载：18/0  |  提交时间：2013/10/08
基于OCR信息的JBIG2编码算法 期刊论文
2010, 2010
尚俊卿; 刘长松; 丁晓青; SHANG Junqing; LIU Changsong; DING Xiaoqing
收藏  |  浏览/下载：6/0
Lossy JBIG2 based on optical character recognition 期刊论文
2010, 2010
Shang Junqing; Liu Changsong; Ding Xiaoqing
收藏  |  浏览/下载：6/0
Infinity-Norm Rotation Transforms 期刊论文
ieee transactions on signal processing, 2009
Yang, Lei; Hao, Pengwei
收藏  |  浏览/下载：3/0  |  提交时间：2015/11/12
Hyperspectral Image Lossy-to-Lossless Compression Using the 3D Embedded ZeroBlock Coding Alogrithm 会议论文
作者:  Hou, Ying;  Liu, Guizhong
收藏  |  浏览/下载：5/0  |  提交时间：2019/12/18
Lossy-to-Lossless Compression of Hyperspectral Imagery Using Three-Dimensional TCE and an Integer KLT 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008, 卷号: 5, 期号: 4, 页码: 814-818
作者:  Zhang, Jing;  Fowler, James E.;  Liu, Guizhong
收藏  |  浏览/下载：1/0  |  提交时间：2019/12/18
Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
Zhao X.; Wei J.; Zhai L.; Liu H.
收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25
An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image  thus facilitating accurate diagnosis  of course at the expense of higher bit rates  i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization  wavelet coding  neural networks  and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1  or even more)  they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image  but the achievable compression ratios are only of the order 2:1  up to 4:1. In our paper  we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time  we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance  so that all the low rate codes are included at the beginning of the bit stream. Typically  the encoding process stops when the target bit rate is met. Similarly  the decoder can interrupt the decoding process at any point in the bil stream  and still reconstruct the image. Therefore  a compression scheme generating an embedded code can start sending over the network the coarser version of the image first  and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.  
JPEG2000嵌入式块编码器架构设计与实现研究 学位论文
2006, 2006
林伟
收藏  |  浏览/下载：5/0  |  提交时间：2016/02/14
数字视频快速浏览、无损编码和物体分割算法的研究 学位论文
博士, 中国科学院声学研究所: 中国科学院声学研究所, 2005
夏杰
收藏  |  浏览/下载：14/0  |  提交时间：2011/05/07

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