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浏览/检索结果: 共6条，第1-6条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Research on algorithm of image reversible watermarking based on compressed sensing 期刊论文 Journal of Information and Computational Science, 2013, 卷号: 10, 期号: 3, 页码: 701-709 作者:  Zhang, Qiuyu;  Sun, Yuan;  Yan, Yan;  Liu, Hongguo;  Shang, Qichang 收藏  |  浏览/下载：13/0  |  提交时间：2020/11/14 Algorithms  Compressed sensing  Image compression  Robustness (control systems)  Signal reconstruction  Watermarking  Arnold scrambling  Blind extraction  Cover-image  Digital image  High quality  Host images  Integer wavelet transforms  Reconstruction algorithms  Reversible watermarking  Reversible watermarking algorithm  Watermark images  Watermarked images  Watermarking systems   Research of high-speed railway image noise removal based on fast recursive GCV threshold function 会议论文 Chengdu, China, June 12, 2010 - June 13, 2010 作者:  Ma, Hongfeng;  Dang, Jianwu;  Liu, Xin 收藏  |  浏览/下载：14/0  |  提交时间：2020/11/15 Agriculture  Railroad cars  Railroad transportation  Railroads  Wavelet decomposition  Complex algorithms  Guiding significances  High  speed railways  High speed train (HST)  Integer wavelet transforms  Recursive operations  Threshold functions  Wavelet threshold de-noising   Hyperspectral image lossless compression using the 3D set partitioned embedded zero block coding alogrithm 会议论文 作者:  Ying, Hou;  Guizhong, Liu 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/18 Bitplane coding  Coding performance  Image lossless compression  Integer wavelet  Integer wavelet transforms  Lossless compression  Memory requirements  Zeroblock coding   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.   Detection and tracking of low contrast targets based on integertype lifting wavelet transform (EI CONFERENCE) 会议论文 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Wang L.; Shen X.; Wang Y. 收藏  |  浏览/下载：11/0  |  提交时间：2013/03/25 This paper presents a method for detecting and tracking of low contrast targets. The new method uses an integer-type lifting wavelet transform and the proposed method doesn't extract patterns similar to a template  but finds parts having the same feature in the targets. We utilize one of integer-type lifting wavelet transforms that contains rounding-off arithmetic for mapping integers to integers. The lifting term contains parameters that are learned by using standard training images of targets. We assume that the targets include many high frequency components. In order to obtain the features of the targets  the lifting parameters are determined by a condition that high frequency components are vanished in wavelet transform. But the condition cannot be determined by the parameters wholly. So  we put an additional condition of minimizing the squared sum of the lifting parameters. The advantage of using integer-type wavelet transform is simple and robust to noise. Simulation illustrated the approach can detect and track the moving targets in dim background. We would test our algorithm in the TV tracking system.   Matrix factorizations for reversible integer mapping 期刊论文 ieee transactions on signal processing, 2001 Hao, PW; Shi, QY 收藏  |  浏览/下载：4/0  |  提交时间：2015/11/10 lifting scheme  linear transforms  lossless compression  matrix factorization  reversible integer mapping  WAVELET TRANSFORMS  LOSSLESS  COMPRESSION