2D filter design for coding artifacts reduction using structural similarity as a metric
Kodai Ogawa, Yusuke Kameda, Yasuyo Kita, Ichiro Matsuda, Susumu Itoh · 2021
This paper describes a method of designing a 2D post filter for reducing coding artifacts caused by lossy image compression. Though Mean Squared Error (MSE) has been typically used in such filter design, it is not necessarily a good quality measure in terms of consistency with subjective perception. In this paper, we employ a more reliable quality measure called Structural SIMilarity (SSIM), and derive filter coefficients that can maximize the SSIM score for each image.