TY - GEN
T1 - CNN-based super-resolution adapted to quantization parameters
AU - Hori, Toshiya
AU - Gong, Zichen
AU - Watanabe, Hiroshi
AU - Ikai, Tomohiro
AU - Chujoh, Takeshi
AU - Sasaki, Eiichi
AU - Ito, Norio
N1 - Publisher Copyright:
© 2020 SPIE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - In video transmission, the videos are encoded and decoded. At that time, bit control is performed by specifying the quantization parameter (QP). The video undergoes various processing to remove redundancy and then orthogonally transforms the video signal into the frequency domain. The frequency domain coefficients are then quantized and transmitted. At that time, by specifying QP, the quantization step is changed, and the amount of data can be changed. In an opinion, a codec using super-resolution is proposed. At the CNN based super-resolution of encoded images, the degradation of the input image due to encoding depends on the characteristics of the image. As a result, there is a problem that the weights of the optimal CNN for the input image changes depending on the image characteristics. In order to solve this problem, we propose a method to adaptively perform super-resolution corresponding to image degradation.
AB - In video transmission, the videos are encoded and decoded. At that time, bit control is performed by specifying the quantization parameter (QP). The video undergoes various processing to remove redundancy and then orthogonally transforms the video signal into the frequency domain. The frequency domain coefficients are then quantized and transmitted. At that time, by specifying QP, the quantization step is changed, and the amount of data can be changed. In an opinion, a codec using super-resolution is proposed. At the CNN based super-resolution of encoded images, the degradation of the input image due to encoding depends on the characteristics of the image. As a result, there is a problem that the weights of the optimal CNN for the input image changes depending on the image characteristics. In order to solve this problem, we propose a method to adaptively perform super-resolution corresponding to image degradation.
KW - Quantization Parameter
KW - Super-resolution
KW - Video Coding
UR - http://www.scopus.com/inward/record.url?scp=85086632092&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086632092&partnerID=8YFLogxK
U2 - 10.1117/12.2566911
DO - 10.1117/12.2566911
M3 - Conference contribution
AN - SCOPUS:85086632092
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - International Workshop on Advanced Imaging Technology, IWAIT 2020
A2 - Lau, Phooi Yee
A2 - Shobri, Mohammad
PB - SPIE
T2 - International Workshop on Advanced Imaging Technology, IWAIT 2020
Y2 - 5 January 2020 through 7 January 2020
ER -