Multi-Frame Image Denoising Based on Minimum Noise Variance Convex Combination with Difference-Based Noise Variance Estimation
Akira Tanaka, Katsuya Kohno · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · 2013
In this paper, we propose a novel multi-frame image denoising technique, which achieves the minimum variance of noise. Zero-mean and unknown variance white noise with an arbitrary distribution is considered in this paper. The proposed method consists of two parts. The first one is the estimation of the variance of noise for each image by considering the differences of all pairs of images. The second one is an actual denoising process in which the convex combination of all images with weight coefficients determined by the estimated variances is constructed. We also give an efficient algorithm by which we can obtain the same result by successive convex combinations. The efficacy of the proposed method is confirmed by computer simulations.