Image Regularization with Total Variation and Optimized Morphological Gradient Priors

Shoya OOHARA  Mitsuji MUNEYASU  Soh YOSHIDA  Makoto NAKASHIZUKA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E102-A   No.12   pp.1920-1924
Publication Date: 2019/12/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E102.A.1920
Type of Manuscript: Special Section LETTER (Special Section on Smart Multimedia & Communication Systems)
Category: Image
Keyword: 
mathematical morphology,  image denoising,  genetic algorithm,  

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Summary: 
For image restoration, an image prior that is obtained from the morphological gradient has been proposed. In the field of mathematical morphology, the optimization of the structuring element (SE) used for this morphological gradient using a genetic algorithm (GA) has also been proposed. In this paper, we introduce a new image prior that is the sum of the morphological gradients and total variation for an image restoration problem to improve the restoration accuracy. The proposed image prior makes it possible to almost match the fitness to a quantitative evaluation such as the mean square error. It also solves the problem of the artifact due to the unsuitability of the SE for the image. An experiment shows the effectiveness of the proposed image restoration method.