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Blind Image Deblurring via Adaptive Optimization with Flexible Sparse St rue ture Control
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作者 Ri-Sheng Liu Cai-Sheng Mao +1 位作者 Zhi-Hui Wang Hao-Jie Li 《Journal of Computer Science & Technology》 SCIE EI CSCD 2019年第3期609-621,共13页
Blind image deblurring is a long-standing ill-posed inverse problem which aims to recover a latent sharp image given only a blurry observation.So far,existing studies have designed many effective priors w.r.t.the late... Blind image deblurring is a long-standing ill-posed inverse problem which aims to recover a latent sharp image given only a blurry observation.So far,existing studies have designed many effective priors w.r.t.the latent image within the maximum a posteriori(MAP)framework in order to narrow down the solution space.These non-convex priors are always integrated into the final deblurring model,which makes the optimization challenging.However,due to unknown image distribution,complex kernel structure and non-uniform noises in real-world scenarios,it is indeed challenging to explicitly design a fixed prior for all cases.Thus we adopt the idea of adaptive optimization and propose the sparse structure control(SSC)for the latent image during the optimization process.In this paper,we only formulate the necessary optiinization constraints in a lightweight MAP model with no priors.Then we develop an inexact projected gradient scheme to incorporate flexible SSC in MAP inference.Besides Zp-norm based SSC in our previous work,we also train a group of denoising convolutional neural networks(CNNs)to learn the sparse image structure automatically from the training data under different noise levels,and we show that CNNs-based SSC can achieve similar results compared with Zp-norm but are more robust to noise.Extensive experiments demonstrate that the proposed adaptive optimization scheme with two types of SSC achieves the state-of-the-art results on both synthetic data and real-world images. 展开更多
关键词 BLIND image DEBLURRING conv olutio nal neural net work(CNN) non-convex optimization SPARSE structure control(SSC)
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