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There exists an intrinsic relationship between the spectral sensitivity ofthe Human Visual System (HVS) and colour perception; these intertwinedphenomena are often overlooked in perceptual compression research. In general,most previously proposed visually lossless compression techniques exploitluminance (luma) masking including luma spatiotemporal masking, luma contrastmasking and luma texture/edge masking. The perceptual relevance of color in apicture is often overlooked, which constitutes a gap in the literature. Withregard to the spectral sensitivity phenomenon of the HVS, the color channels ofraw RGB 4:4:4 data contain significant color-based psychovisual redundancies.These perceptual redundancies can be quantized via color channel-levelperceptual quantization. In this paper, we propose a novel spatiotemporalvisually lossless coding method named Spectral Perceptual Quantization(Spectral-PQ). With application for RGB 4:4:4 video data, Spectral-PQ exploitsHVS spectral sensitivity-related color masking in addition to spatial maskingand temporal masking; the proposed method operates at the Coding Block (CB)level and the Prediction Unit (PU) level in the HEVC standard. Spectral-PQperceptually adjusts the Quantization Step Size (QStep) at the CB level if highvariance spatial data in G, B and R CBs is detected and also if high motionvector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17RExt), Spectral-PQ considerably reduces bitrates with a maximum reduction ofapproximately 81%. The Mean Opinion Score (MOS) in the subjective evaluationsshow that Spectral-PQ successfully achieves perceptually lossless quality.

Spectral-PQ: A Novel Spectral Sensitivity-Orientated Perceptual Compression Technique for RGB 4:4:4 Video Data