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JND-Guided Perceptual Pre-filtering for HEVC Compression of UHDTV Video Contents

Eloïse Vidal 1, 2 François-Xavier Coudoux 1, 2 Patrick Corlay 1, 2 Christine Guillemot 
2 COMNUM - IEMN - COMmunications NUMériques - IEMN
IEMN-DOAE - Institut d’Électronique, de Microélectronique et de Nanotechnologie - Département Opto-Acousto-Électronique - UMR 8520
Abstract : In this paper, two new perceptual filters are presented as pre-processing techniques to reduce the bitrate of HEVC compressed Ultra high-definition (UHD) video contents at constant visual quality. The proposed perceptual filters rely on two novel adaptive filters (called BilAWA and TBil) which combine the good properties of the bilateral and Adaptive Weighted Averaging (AWA) filters. Moreover, these adaptive filters are guided by a just-noticeable distortion (JND) model to adaptively control the strength of the filtering process, taking into account the properties of the human visual system. Extensive psychovisual evaluation tests conducted on several UHD-TV sequences are presented in detail. Results show that applying the proposed pre-filters prior to HEVC encoding of UHD video contents lead to bitrate savings up to 23% for the same perceived visual quality.
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Submitted on : Friday, February 11, 2022 - 11:04:33 AM
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Eloïse Vidal, François-Xavier Coudoux, Patrick Corlay, Christine Guillemot. JND-Guided Perceptual Pre-filtering for HEVC Compression of UHDTV Video Contents. Lecture Notes in Computer Science, Springer, 2017, Lecture Notes in Computer Science, 10617, pp.375-385. ⟨10.1007/978-3-319-70353-4_32⟩. ⟨hal-03565787⟩



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