Mean Saving-Cost Ratio: A Metric for Evaluating the Impact of Image Preprocessing on the Rate-Distortion Performance of Video Encoding
Feb 10, 2023·
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Markus Hofbauer
Christopher kuhn
Goran petrovic
Eckehard steinbach
Image credit: IEEEAbstract
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.
Type
Publication
In Encyclopedia with Semantic Computing and Robotic Intelligence

Authors
Markus Hofbauer
(he/him)
Software Engineer - Developer Productivity & Associate Lecturer
Markus is part of the Developer Productivity Engineering team at Zipline.
They develop and maintain the build system, developer tooling, and the CI/CD system to enable other developers to build and release high-quality software products.
Markus received his PhD in Electrical and Computer Engineering from the Technical University of Munich where he is still teaching principles of software engineering to students.
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