Blind image restoration based on normalized hyper laplacian prior term

Guodong, 王国栋 Wang; Jie, 徐洁 Xu; Zhenkuan, 潘振宽 Pan; Cun-liang, 刘存良 Liu; Jin-bao, 杨金宝 Yang

doi:10.3788/ope.20132105.1340

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“…The restored image has got the motion de-blur effect. Besides, the convolution kernel function is very smooth, which is in the line with the characteristics of the motion blur camera [10] .…”

Section: Experimental Results and Analysissupporting

confidence: 54%

An Improved Blind Deconvolution Algorithm of Motion Blurred Image

Yang

Wang

Hui

et al. 2014

AMM

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An improved blind deconvolution algorithm has been proposed to tackle the image blurring caused by movement. Firstly, take the model to analyze the blurred image and identify the high-frequency of the blurred image through the reasonable pre-estimation of blind kernel function. Then, further estimate the blurring matrix K by the use of the high-frequency while the high-frequency of the blurred image and the accuracy of the blurred image matrix have been improved gradually through normalized iteration. Finally, the clear image has been gained by the use of blind matrix deconvolution. Experimental results show that by the use of this algorithm the image has better subjective visual effect. The proposed algorithm has better restoration effect on the fused motion blurred image and the natural camera motion blurred image.

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Section: Experimental Results and Analysissupporting

confidence: 54%