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Towards the Perceptual Quality Enhancement of Low Bit-Rate Compressed Images
AbstractIn 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. To show that the reconstructed images has enhanced visual quality, we have used the objective quality metric. The experimental results presents that the proposed framework shows significant improvement in the human visual quality and a 33% improvement in the objective evaluation criterion of the perceptual quality.
Related Material
[pdf][bibtex]@InProceedings{Kim_2020_CVPR_Workshops,
author = {Kim, Younhee and Cho, Seunghyun and Lee, Jooyoung and Jeong, Se-Yoon and Choi, Jin Soo and Do, Jihoon},
title = {Towards the Perceptual Quality Enhancement of Low Bit-Rate Compressed Images},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2020}
}
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