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CORC

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Gated Feature Aggregation for Height Estimation From Single Aerial Images 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5
作者:  Xing, Siyuan;  Dong, Qiulei;  Hu, Zhanyi
收藏  |  浏览/下载：22/0  |  提交时间：2022/01/27
Progressive rectification network for irregular text recognition 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 2, 页码: 1-14
作者:  Gao, Yunze;  Chen, Yingying;  Wang, Jinqiao;  Lu, Hanqing
收藏  |  浏览/下载：8/0  |  提交时间：2020/04/07
Multi-Layer Progressive Face Alignment by Integrating Global Match and Local Refinement 期刊论文
APPLIED SCIENCES-BASEL, 2019, 卷号: 9
作者:  Gao, Ning;  Wang, Xingyuan;  Wang, Xiukun
收藏  |  浏览/下载：2/0  |  提交时间：2019/12/02
Cloud Detection of RGB Color Aerial Photographs by Progressive Refinement Scheme 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 卷号: 52, 期号: 11
作者:  Zhang, Qing;  Xiao, Chunxia
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/05
Efficient monitoring of skyline queries over distributed data streams 期刊论文
knowledge and information systems, 2010
Sun, Shengli; Huang, Zhenghua; Zhong, Hao; Dai, Dongbo; Liu, Hongbin; Li, Jinjiu
收藏  |  浏览/下载：1/0  |  提交时间：2015/11/10
efficient monitoring of skyline queries over distributed data streams 期刊论文
KNOWLEDGE AND INFORMATION SYSTEMS, 2010, 卷号: 25, 期号: 3, 页码: 575-606
Sun Shengli; Huang Zhenghua; Zhong Hao; Dai Dongbo; Liu Hongbin; Li Jinjiu
收藏  |  浏览/下载：20/0  |  提交时间：2011/05/23
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：29/0  |  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.  
A new compression scheme for color-quantized images 期刊论文
ieee transactions on circuits and systems for video technology, 2002
Chen, X; Kwong, S; Feng, JF
收藏  |  浏览/下载：4/0  |  提交时间：2015/11/10

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