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单小波去噪方法在多小波去噪中的应用研究 总被引:3,自引:0,他引:3
单小波去噪方法中Visualshrink去噪法是渐进最优的。但将'Visualshrink单小波去噪方法用于多小波去噪,其优越性丧失,图象中存在严重的Gibbs效应,且去噪效果降低,对此,我们改进了单小波Visualshrink去噪方法的门限选取,提出了改进的Visualshrink多小波去噪方法(VMD)。同时,还给出了离散多小波变换的具体实现方法。实验结果证明,改进的多小波去噪方法与直接将Visualshrink方法用于多小波去噪相比,前者效果明显好于后者。 相似文献
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Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information. 相似文献
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遗传算法的进展与展望 总被引:7,自引:0,他引:7
遗传算法作为一种新的优化搜索方法,被广泛应用于许多优化问题,本文对遗传算法进行了简要概述,主要讲述了遗传算法的特点、现状及进展,并阐述了遗传算法的最新研究领域及未来研究课题。 相似文献
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小波变换用于图像去噪的思想已经提出了很久,然而前人所提出的这种方法对于去噪的效果并不理想。图 像经这种小波变换去噪后,纹理特征被弱化,图像的边缘出现较明显的Gibbs效应,图像变模糊。针对以上问题,本文提 出了一种高效的小波变换去噪方法(HPID)。此去噪方法是基于小波变换的新方法,与经典的小波去噪方法不同,该方法不 依赖图像大小来判定去噪门限,不需方差信息,且适用于不同类型噪声。采用本方法处理的噪声图像与经典方法相比,不 仅消除了Gibbs效应,而且图像的边缘信息更清晰,纹理特征增强,去噪能力得到改善。 相似文献
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Deviation is essential to classic soft threshold denoising in wavelet domain. Texture features of noised image denoised by wavelet transform were weakened. Gibbs effect is distinct at edges of image.Image blurs comparing with original noised image. To solve the questions, a blind denoising method based on single-wavelet transform and multiwavelets transform was proposed. The method doesn't depend on size of image and deviation to determine threshold of wavelet coefficients, which is different from classical soft-threshold denoising in wavelet domain. Moreover, the method is good for many types of noise. Gibbs effect disappeared with this method, edges of image are preserved well, and noise is smoothed and restrained effectively. 相似文献
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