Weights-Based Image Demosaicking Using Posteriori Gradients and the Correlation of R–B Channels in High Frequency

Abstract

In this paper, we propose a weights-based image demosaicking algorithm which is based on the Bayer pattern color filter array (CFA). When reconstructing the missing G components, the proposed algorithm uses weights based on posteriori gradients to mitigate color artifacts and distortions. Furthermore, the proposed algorithm makes full use of the correlation of R–B channels in high frequency when interpolating R/B values at B/R positions. Experimental results show that the proposed algorithm is superior to previous similar algorithms in composite peak signal-to-noise ratio (CPSNR) and subjective visual effect. The biggest advantage of the proposed algorithm is the use of posteriori gradients and the correlation of R–B channels in high frequency.

Research on the Modulation Transfer Function Detection Method of a Bayer Filter Color Camera

“…Each pixel of the image obtained by the Bayer array has only one color gray value, and the process of using the surrounding pixels to estimate the two colors missing from the pixel in question is called color synthesis, also known as the demosaicing process. The most commonly used interpolation algorithms for color synthesis are the bilinear interpolation algorithm [24], the color smoothing interpolation algorithm [25], and the adaptive interpolation algorithm [26]. The bilinear interpolation algorithm is the most basic color synthesis algorithm and provides a good reference for other algorithms.…”