SVMs Interpolation Based Edge Correction Scheme for Color Filter Array

Abstract

To settle the problem of blurring and visible artifacts around the edge regions of color filter array (CFA) interpolation images, a Support Vector Machines (SVMs) interpolation based edge correction scheme is proposed. In this scheme, a simple CFA interpolation method is used, and the support vector regression (SVR) is trained to rectify the color values at the edge of the result image. This scheme can produce visually pleasing full-color images and obtain better PSNR results than other conventional CFA interpolation algorithms. The correction is concentrated on the edge region, because the human perception is mainly focusing on edge region. The scheme can reduce the training time effectively, and can combine with other CFA interpolation algorithms freely. Simulation studies indicate that the proposed algorithm is effective.