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Conference Paper Towards the Perceptual Quality Enhancement of Low Bit-rate Compressed Images
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Authors
Younhee Kim, Seunghyun Cho, Jooyoung Lee, Se-Yoon Jeong, Jin Soo Choi, Jihoon Do
Issue Date
2020-06
Citation
Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2020, pp.565-569
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/CVPRW50498.2020.00076
Abstract
In this paper, a low bit-rate compressed image quality enhancement framework is presented. A recent image/video coding method and a deep learning based quality enhancement method are integrated to improve the perceptual quality of compressed images. The proposed architecture is designed to reduce the coding artifact and restore the blurred texture details. The experimental results presents that the proposed framework yields a 33% improvement in the Perceptual Index score which is consistent with visual evaluation on a sample of results.
KSP Keywords
Coding method, Enhancement framework, Enhancement method, Image quality enhancement, Perceptual Quality, Visual evaluation, compressed images, deep learning(DL), low bit rate, video coding