Learning from Ideal Edge for Image Restoration

Jin-Ping HE  Kun GAO  Guo-Qiang NI  Guang-Da SU  Jian-Sheng CHEN  

IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.11   pp.2487-2491
Publication Date: 2013/11/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.2487
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
learning-based,  image restoration,  ideal edge,  image analogy,  

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Considering the real existent fact of the ideal edge and the learning style of image analogy without reference parameters, a blind image recovery algorithm using a self-adaptive learning method is proposed in this paper. We show that a specific local image patch with degradation characteristic can be utilized for restoring the whole image. In the training process, a clear counterpart of the local image patch is constructed based on the ideal edge assumption so that identification of the Point Spread Function is no longer needed. Experiments demonstrate the effectiveness of the proposed method on remote sensing images.