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  4. A spectrally adaptive noise filling tool for perceptual transform coding of still images
 
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2018
Conference Paper
Title

A spectrally adaptive noise filling tool for perceptual transform coding of still images

Abstract
Modern perceptual image coders reach impressively high subjective quality even at low bit-rates but tend to denoise or ""detexturize"" the coded pictures. Traditionally, two independent parametric approaches, known as texture and film grain synthesis, have been applied in the spatial domain as pre and post-processors around the codec to counteract such effects. In this work, a unified alternative, operating directly within the spectral domain of conventional transform codecs with tight coupling to the transform coefficient quantizer, is proposed. Due to its design, this spectrally adaptive noise filling tool (SANFT) enables highly input adaptive realizations by reusing the coder's existing optimized spatial and spectral partitioning algorithms. Formal subjective evaluation in the context of a main still picture"" High Emciency Video Coding (HEVC) implementation confirms the benefit of the proposal.
Author(s)
Helmrich, C.R.
Bosse, S.
Keydel, P.
Schwarz, H.
Marpe, D.
Wiegand, T.
Mainwork
IEEE 8th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018. Proceedings  
Conference
International Conference on Consumer Electronics - Berlin (ICCE-Berlin) 2018  
DOI
10.1109/ICCE-Berlin.2018.8576238
Language
English
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
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