Generation of reference images using filtered radon transform and truncated SVD for structural artifacts

Abstract

Image quality assessment (IQA) is an effective way to evaluate image/signal processes (ISPs). Here, we present a single value decomposition (SVD)-based IQA method to quantitatively evaluate morphological distortion of chessboard patterns. Incorrect ISP tuning parameters can create suboptimal images with artifacts on the edges of small text or high-frequency patterns. We reproduced those artifacts by using a small chessboard pattern and quantitatively evaluated the morphological distortion in the pattern. Then, we verified our method through qualitative evaluation survey and Pearson correlation. As a result, the score of the proposed method was in good agreement with the qualitative evaluation result and had a Pearson correlation coefficient (PCC) of 0.97.