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	<title>छवि बहाली के लिए केंद्रीकृत स्पैस प्रतिनिधित्व Archives &#8212; MATLAB Number ONE</title>
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		<title>Centralized sparse representation for image restoration</title>
		<link>https://matlab1.com/shop/matlab-code/centralized-sparse-representation-for-image-restoration/</link>
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		<pubDate>Mon, 16 Apr 2018 03:20:10 +0000</pubDate>
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					<description><![CDATA[<p>Image restoration (IR) is a fundamental topic in image processing and computer vision applications, and it has been widely studied. In this paper, we investigated IR with the sparse coding techniques. To better understand the effectiveness of sparse coding for IR, we introduced the concept of sparse coding noise (SCN), and it was empirically found that SCN follows Laplacian distributions. To [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/centralized-sparse-representation-for-image-restoration/">Centralized sparse representation for image restoration</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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