To solve the problem of the detection and segment of local blur image,a local blur detection method based on re-blur theory and singular value decomposition is proposed.Firstly,the test image is pro-cessed by Gaussian Blur and continuously segmented,and the test image blocks are decomposed by singular value decomposition.Secondly,the singular value vector of every image block is fitted by exponential func-tion to get the singular value curve of the images to be measured and re-blured images.Then,the integral of singular value vector of image blocks are counted respectively and being subtracted,and the difference of subtraction of integral value is used as blur feature.Finally,the canny edge detection algorithm is used to complete the image segmentation and use the maximum and minimum filters and related morphological pro-cessing to deal with the internal area of the edge.The experiment results show that the method can effective-ly complete the detection and segmentation of local blur image,and it is also effective in the identification of flat regions of texture.
关键词
模糊检测/再模糊理论/奇异值分解/拟合曲线积分/模糊特征
Key words
blur detection/re-blur theory/singular value decomposition/curve fitting integral/blur feature
维普
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