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Conference Paper Perceptual Video Coding using Deep Neural Network Based JND Model
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Authors
Jongho Kim, Dae Yeol Lee, Seyoon Jeong, Seunghyun Cho
Issue Date
2020-03
Citation
Data Compression Conference (DCC) 2020, pp.375-375
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/DCC47342.2020.00087
Project Code
20HH2300, Development of Audio/Video Coding and Light Field Media Fundamental Technologies for Ultra Realistic Tera-media, Choi Jin Soo
Abstract
We propose a perceptual video coding (PVC) method that uses the deep neural network (DNN) based just noticeable difference (JND) suppression model. The proposed JND suppression model's goal is to reduce the perceptual redundancy of the input video prior to the encoding process through a DNN, and further improve the compression efficiency while minimally affecting the perceptual quality.
KSP Keywords
Deep neural network(DNN), Just noticeable difference(JND), Perceptual Quality, Perceptual video coding, compression efficiency, encoding process