Target self-adaptive hiding method based on feature space statistical information mapping
The invention provides a target self-adaptive hiding method based on feature space statistical information mapping. The method comprises: using a deep convolution learning mode, on the basis of target and background region division by using significance target detection, respectively obtaining a tar...
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creator | LI CE ZHU ZIZHONG GAO WEIZHE JIN SHANGANG ZHANG DONG LIU HAO JIA SHENGZE XU DAYOU LI LAN |
description | The invention provides a target self-adaptive hiding method based on feature space statistical information mapping. The method comprises: using a deep convolution learning mode, on the basis of target and background region division by using significance target detection, respectively obtaining a target feature space and feature space statistical information representing background style features, establishing a mapping network of the feature space statistical information between a target image and a background region image, the target image having the feature space statistical information of the background region image, and obtaining a target self-adaptive hidden image through boundary fusion. According to the method, the mapping network about the characteristic space statistical information between the target image and the background area image is established, the task target of target self-adaptive hiding is carried out, a corresponding solution is provided for the task target, a good result is obtained, an |
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The method comprises: using a deep convolution learning mode, on the basis of target and background region division by using significance target detection, respectively obtaining a target feature space and feature space statistical information representing background style features, establishing a mapping network of the feature space statistical information between a target image and a background region image, the target image having the feature space statistical information of the background region image, and obtaining a target self-adaptive hidden image through boundary fusion. 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The method comprises: using a deep convolution learning mode, on the basis of target and background region division by using significance target detection, respectively obtaining a target feature space and feature space statistical information representing background style features, establishing a mapping network of the feature space statistical information between a target image and a background region image, the target image having the feature space statistical information of the background region image, and obtaining a target self-adaptive hidden image through boundary fusion. 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The method comprises: using a deep convolution learning mode, on the basis of target and background region division by using significance target detection, respectively obtaining a target feature space and feature space statistical information representing background style features, establishing a mapping network of the feature space statistical information between a target image and a background region image, the target image having the feature space statistical information of the background region image, and obtaining a target self-adaptive hidden image through boundary fusion. According to the method, the mapping network about the characteristic space statistical information between the target image and the background area image is established, the task target of target self-adaptive hiding is carried out, a corresponding solution is provided for the task target, a good result is obtained, an</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
title | Target self-adaptive hiding method based on feature space statistical information mapping |
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