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	Wavelet bi-frames with uniform symmetry 期刊论文 iSwitch采集 Mathematical methods in the applied sciences, 2016, 卷号: 39, 期号: 13, 页码: 3701-3721 作者: Li, Baobin 收藏 \| 浏览/下载：38/0 \| 提交时间：2019/05/09 Wavelet bi-frames Frames Frame filter banks Lifting scheme
	Detection of low contrast targets based on lifting scheme wavelet transform (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, August 9, 2009 - August 12, 2009, Changchun, China 作者: Chen X.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 This paper present a fast algorithm for detection of low contrast objects by using wavelet filters based on lifting scheme. The advantage is robust to noise. According Swelden's lifting wavelet filters are biorthogonal wavelet filters containing free parameters. We use reference image of targets to train the lifting terms so that the learnt wavelet filters have the features of targets. Then applying such filters to the images including targets taken from camera system. We can detect the locations where the high frequency components are almost the same as those of the target image. 2009 IEEE.
	Two-step single parameter regularization Fisher discriminant method for face recognition 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2006, 卷号: 20, 期号: 2, 页码: 189-207 作者: Chen, WS; Yuen, PC; Huang, J; Fang, B \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2018/07/30 face recognition Fisher discriminant analysis small sample size problem rank lifting scheme
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：53/0 \| 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.
	Image compression based on biorthogonal wavelet transform (EI CONFERENCE) 会议论文 OAI收割 ISCIT 2005 - International Symposium on Communications and Information Technologies 2005, October 12, 2005 - October 14, 2005, Beijing, China 作者: Gao Y.; Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 A method for image compression of biorthogonal wavelet transform based on lifting scheme with SPIHT (Set Partitioning In Hierachical Trees) is proposed in this paper. Wavelet transform affords wide space for image coding algorithms because of its excellent space-frequency localization characterizations. The compact supported symmetrical and biorthogonal wavelet has linear phase so it is applied on image compression area widely. The lifting scheme is an efficient method for constructing the wavelet filter after multiresolution. Under the condition of biorthogonal biorthogonal wavelet base can be constructed freely according to the wavelet performance. And it can quicken the implementation speed of the wavelet transform. Analyzing the algorithm of lifting scheme is applying for constructing biorthogonal wavelet. Experimental results indicate that the method of the biorthogonal wavelet that has good performances with SPIHT is applying for image compression so as image synthesis performs well. 2005 IEEE.