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	Lifting for the integer knapsack cover polyhedron 期刊论文 OAI收割 JOURNAL OF GLOBAL OPTIMIZATION, 2022, 页码: 45 作者: Chen, Wei-Kun; Chen, Liang; Dai, Yu-Hong \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2023/02/07 Integer programming Cutting plane Sequential lifting MIR inequality Separation algorithm
	XGBoost在气体红外光谱识别中的应用期刊论文 OAI收割光学学报, 2020, 卷号: 40 作者: 刘家祥; 宁志强; 吴越; 方勇华; 陶孟琪 \| 收藏 \| 浏览/下载：47/0 \| 提交时间：2020/10/26 spectroscopy pattern recognition infrared spectroscopy lifting algorithm feature engineering 光谱学模式识别红外光谱提升算法特征工程
	Destriping method using lifting wavelet transform of remote sensing image (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China 作者: He B. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Based on the characteristic of striping noise in remote sensing images a new destriping noise technique for the improved multi-threshold method using lifting wavelet transform applied to remote sensing imagery is presented in this letter. Have used the lifting wavelet decomposition algorithm the thresholds are determined by corresponding wavelet coefficients in every scale. Remote sensing imagery is so large that the algorithm must be fast and effective. The lifting wavelet transform is easily realized and inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the method with some traditional destriping methods both by visual inspection and by appropriate indexes of quality of the denoised images. From the comparison we can see that the adaptive threshold method can preserve the spectral characteristic of the images while effectively remove striping noise and it did better than the existed ones. 2010 IEEE.
	A new image fusion algorithm based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China 作者: He X.; Zhang Y.; Zhang L.-G.; Zhang L.-G. 收藏 \| 浏览/下载：13/0 \| 提交时间：2013/03/25 A new image fusion algorithm based on lifting wavelet transform is presented in this paper. The source images are decomposed using lifting wavelet transform respectively. Aiming at the coefficients of low frequency and high frequency this algorithm choose a different rule to fuse the image. To the low frequency the spatial frequency based on the neighborhood add consistency check is elected as the fusion guide. And the absolute maximum based on detail coefficients is selected as the guide to the high frequency. After that the fused image is obtained by using inverse lifting wavelet transform. Taking the ratio space frequency error and the mean gradient as criterions experimental results demonstrate that the algorithm is very effective. 2010 IEEE.
	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：16/0 \| 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.
	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：41/0 \| 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 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang L.; Wang L.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：18/0 \| 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.
	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：33/0 \| 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.