Measuring the Influence of Image Preprocessing on the Rate-Distortion Performance of Video Encoding

Abstract

In image and video coding, preprocessing of the images allows to increase the perceptual quality or to control the bitrate. In this paper, we conduct an extensive analysis of the rate-distortion (RD) performance achieved by using different preprocessing steps before encoding the video. We propose a novel evaluation method called the Mean Saving-Cost Ratio (MSCR) to compare the RD performance for different preprocessing algorithms. We define MSCR as the logarithmic mean ratio of maximum bitrate savings over maximum quality cost for all parameters of a preprocessing algorithm. Further, we calculate the Bjontegaard Delta Rate for every quantization parameter (QP) between two RD curves at the respective QP. The resulting Bjontegaard Delta curves allow for comparing two preprocessing algorithms over a range of QPs. In our experiments, we use the proposed MSCR to compare different preprocessing algorithms such as a Gaussian low-pass filter, a median filter, and a JPEG compressor. Overall, the Gaussian low-pass filter shows the best RD performance according to MSCR.

Markus Hofbauer

Senior Build Engineer & Associate Lecturer

Senior Build Engineer at Luminar Technologies and Associate Lecturer on Software Engineering at the Technical University of Munich.