TY - GEN
T1 - Perceptual Quality Study on Deep Learning Based Image Compression
AU - Cheng, Zhengxue
AU - Akyazi, Pinar
AU - Sun, Heming
AU - Katto, Jiro
AU - Ebrahimi, Touradj
N1 - Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/9
Y1 - 2019/9
N2 - Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation on such compression schemes have rarely been reported. This paper aims at perceptual quality studies on learned compression. First, we build a general learned compression approach, and optimize the model. In total six compression algorithms are considered for this study. Then, we perform subjective quality tests in a controlled environment using high-resolution images. Results demonstrate learned compression optimized by MS-SSIM yields competitive results that approach the efficiency of state-of-the-art compression. The results obtained can provide a useful benchmark for future developments in learned image compression.
AB - Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation on such compression schemes have rarely been reported. This paper aims at perceptual quality studies on learned compression. First, we build a general learned compression approach, and optimize the model. In total six compression algorithms are considered for this study. Then, we perform subjective quality tests in a controlled environment using high-resolution images. Results demonstrate learned compression optimized by MS-SSIM yields competitive results that approach the efficiency of state-of-the-art compression. The results obtained can provide a useful benchmark for future developments in learned image compression.
KW - Subjective and objective quality evaluation
KW - compression standards
KW - learning image compression
UR - http://www.scopus.com/inward/record.url?scp=85076800720&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076800720&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2019.8803824
DO - 10.1109/ICIP.2019.8803824
M3 - Conference contribution
AN - SCOPUS:85076800720
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 719
EP - 723
BT - 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
PB - IEEE Computer Society
T2 - 26th IEEE International Conference on Image Processing, ICIP 2019
Y2 - 22 September 2019 through 25 September 2019
ER -