Weight Optimization for Multiple Image Integration and Its Applications

Ryo MATSUOKA  Tomohiro YAMAUCHI  Tatsuya BABA  Masahiro OKUDA  

IEICE TRANSACTIONS on Information and Systems   Vol.E99-D   No.1   pp.228-235
Publication Date: 2016/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2015EDP7192
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
denoising,  convex optimization,  high dynamic range images,  super-resolution,  

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We propose an image restoration technique that uses multiple image integration. The detail of the dark area when acquiring a dark scene is often deteriorated by sensor noise. Simple image integration inherently has the capability of reducing random noises, but it is especially insufficient in scenes that have a dark area. We introduce a novel image integration technique that optimizes the weights for the integration. We find the optimal weight map by solving a convex optimization problem for the weight optimization. Additionally, we apply the proposed weight optimization scheme to a single-image super-resolution problem, where we slightly modify the weight optimization problem to estimate the high-resolution image from a single low-resolution one. We use some of our experimental results to show that the weight optimization significantly improves the denoising and super-resolution performances.