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	<title>共同適応型正規化 Archives &#8212; MATLAB Number ONE</title>
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	<title>共同適応型正規化 Archives &#8212; MATLAB Number ONE</title>
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		<title>Blind Image Quality Prediction Using Joint Statistics of Gradient Magnitude and Laplacian Features</title>
		<link>https://matlab1.com/shop/matlab-code/blind-image-quality-prediction-using-joint-statistics-of-gradient-magnitude-and-laplacian-features/</link>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 16 Apr 2018 06:28:55 +0000</pubDate>
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					<description><![CDATA[<p>Existing BIQA models typically decompose an image into different frequency and orientation bands, and then extract statistical features from the decomposed coefficients to learn a quality prediction model. However, few BIQA models explicitly exploit simple image contrast features such as the gradient magnitude (GM) and Laplacian of Gaussian (LOG) responses, although LOG responses share similarities to human receptive field responses. Here we [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/blind-image-quality-prediction-using-joint-statistics-of-gradient-magnitude-and-laplacian-features/">Blind Image Quality Prediction Using Joint Statistics of Gradient Magnitude and Laplacian Features</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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