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	<title>圖像去噪 Archives &#8212; MATLAB Number ONE</title>
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	<title>圖像去噪 Archives &#8212; MATLAB Number ONE</title>
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		<title>Estimation and Preservation for Texture Enhanced Image Denoising</title>
		<link>https://matlab1.com/shop/matlab-code/gradient-histogram-estimation-and-preservation-for-texture-enhanced-image-denoising/</link>
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		<pubDate>Tue, 08 May 2018 06:09:03 +0000</pubDate>
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					<description><![CDATA[<p>In this project , we presented a novel gradient histogram preservation (GHP) model for texture-enhanced image denoising, and further introduce two region-based GHP variants, i.e., B-GHP and S-GHP. A simple but theoretically solid model and the associated algorithm were presented to estimate the reference gradient histogram from the noisy image, and an efficient iterative histogram specification algorithm was developed to implement the [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/gradient-histogram-estimation-and-preservation-for-texture-enhanced-image-denoising/">Estimation and Preservation for Texture Enhanced Image Denoising</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Active contours driven by local image fitting energy</title>
		<link>https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/</link>
					<comments>https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 19 Apr 2018 06:24:50 +0000</pubDate>
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					<description><![CDATA[<p>&#160;</p>
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<p>The post <a href="https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/">Active contours driven by local image fitting energy</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Multiscale LMMSE-based image denoising with optimal wavelet selection</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 16 Apr 2018 13:53:23 +0000</pubDate>
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					<description><![CDATA[<p>In this paper, we presented an LMMSE-based denoising scheme with a wavelet interscale model and discussed the optimal wavelet basis selection for it. With OWE the wavelet coefficients at the same spatial locations at two adjacent scales are represented as a vector and the LMMSE is applied to the vector. The wavelet interscale dependencies are thus exploited to improve the signal [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/multiscale-lmmse-based-image-denoising-with-optimal-wavelet-selection/">Multiscale LMMSE-based image denoising with optimal wavelet selection</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Image denoising using least squares support vector machine</title>
		<link>https://matlab1.com/shop/matlab-code/image-denoising-using-least-squares-support-vector-machine/</link>
					<comments>https://matlab1.com/shop/matlab-code/image-denoising-using-least-squares-support-vector-machine/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sat, 20 Aug 2016 06:32:11 +0000</pubDate>
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					<description><![CDATA[<p>Link of paper : http://www.sciencedirect.com/science/article/pii/S0952197609001377 &#160; Due to the imperfection of image acquisition systems and transmission channels, images are often corrupted by noise. This degradation leads to a signiﬁcant reduction of image quality and then makes more difﬁcult to perform high-level vision tasks such as recognition, 3-D reconstruction, or scene interpretation. The image denoising is important, [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/image-denoising-using-least-squares-support-vector-machine/">Image denoising using least squares support vector machine</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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