For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Weight Optimization for Multiple Image Integration and Its Applications
Ryo MATSUOKA Tomohiro YAMAUCHI Tatsuya BABA Masahiro OKUDA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2016/01/01
Online ISSN: 1745-1361
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
denoising, convex optimization, high dynamic range images, super-resolution,
Full Text: PDF(1.7MB)>>
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.