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Total Variation Based Parameter-Free Model for Impulse Noise Removal 被引量:3
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作者 Federica Sciacchitano Yiqiu Dong martin s.andersen 《Numerical Mathematics(Theory,Methods and Applications)》 SCIE CSCD 2017年第1期186-204,共19页
We propose a new two-phase method for reconstruction of blurred im-ages corrupted by impulse noise.In the first phase,we use a noise detector to iden-tify the pixels that are contaminated by noise,and then,in the seco... We propose a new two-phase method for reconstruction of blurred im-ages corrupted by impulse noise.In the first phase,we use a noise detector to iden-tify the pixels that are contaminated by noise,and then,in the second phase,we reconstruct the noisy pixels by solving an equality constrained total variation mini-mization problem that preserves the exact values of the noise-free pixels.For images that are only corrupted by impulse noise(i.e.,not blurred)we apply the semismooth Newton’s method to a reduced problem,and if the images are also blurred,we solve the equality constrained reconstruction problem using a first-order primal-dual algo-rithm.The proposed model improves the computational efficiency(in the denoising case)and has the advantage of being regularization parameter-free.Our numerical results suggest that the method is competitive in terms of its restoration capabilities with respect to the other two-phase methods. 展开更多
关键词 Image deblurring image denoising impulse noise noise detector primal-dual first-order algorithm semismooth Newton method total variation regularization
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