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	Fusing remote sensing images using a trous wavelet transform and empirical mode decomposition SCI/SSCI论文 OAI收割 2008 作者: Tian J. 收藏 \| 浏览/下载：37/0 \| 提交时间：2012/06/08 image fusion a trous wavelet transform empirical mode decomposition dyadic wavelet transform intensity modulation reconstruction contrast quality
	A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Hu S.; Zhu M.; Wu C.; Song H.-J. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 In many computer vision tasks in order to improve the accuracy and robustness to the noise wavelet analysis is preferred for the natural multi-resolution property. However the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour the Zernike moments are introduced and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient precise and robust.
	A new approach for the removal of mixed noise based on 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: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.
	Wavelet-fractal based compression of ophthalmic image (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Xiu-Ying Z.; Lin-Pei Z. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 This study is designed to determine the degree and methods of digital image compression to produce ophthalmic images of sufficient quality for transmission and diagnosis. Fractal based compression techniques which provide a large compression ratio for grayscale images have been reported in the literature. Fractal coding is based on the fractal theory of iterated transformations. But it's searching and mapping algorithm cannot address the need of real-time. To improve the real-time performance of the algorithm we use wavelet transforms to decompose images. The wavelet transform is a natural tool for analyzing fractal block coders since wavelet bases possess the same type of dyadic self-similarity that fractal coders seek to exploit. We propose a method of fractal coding the weighted wavelet subtree. Experimented results show that the improved hybrid image can improve the PSNR of the rebuild image at the same compression ratio.
	Application of dyadic wavelet transform modulus maximum method to denoising of capillary electrophoresis signals 期刊论文 OAI收割 CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE, 2002, 卷号: 23, 期号: 5, 页码: 796-800 作者: Zhong, HB; Li, GB; Liu, H; Zheng, JB; Chen, LR \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2019/04/09 Dyadic Wavelet Transform Modulus Maximum De-noise