Perceptual Signal Coding for More Efficient Usage of Bit Codes

Abstract

As the performance of electronic display systems continues to increase, the limitations of current signal coding methods become more and more apparent. With bit depth limitations set by industry standard interfaces, a more efficient coding system is desired to allow image quality to increase without requiring expansion of legacy infrastructure bandwidth. A good approach to this problem is to let the human visual system determine the quantization curve used to encode video signals. In this way optimal efficiency is maintained across the luminance range of interest, and the visibility of quantization artifacts is kept to a uniformly small level.

Objective and subjective evaluation of High Dynamic Range video compression

“…Therefore, an interesting research area which has recently gained traction following the HDR/WCG call for proposals to would be to see how non-backward compatible compression algorithms (including the ones presented in this work) can be adapted to perform with HEVC Main-10 profile [43] for even lower bitrates. Subsequently, the modified non-backward compatible algorithms can be evaluated against the recently adopted Perceptual Quantizer algorithm (SMPTE ST 2084) [31] and Hybrid Log-Gamma algorithm [9] to test and compare their HDR reconstruction performance such as has been considered by François et al [13]. Efficient use of available bandwidth might finally lead to the widespread commercial adoption of HDR.…”

“…The paper concludes that the proposals submitted to MPEG can noticeably improve the standard HDR video coding technology and QA metrics such as PSNR-DE1000, HDR-VDP2 and PSNR-Lx can reliably detect visible difference. Azimi et al [5] conducted a study to evaluate the compression efficiency of two possible HDR video encoding schemes (as defined in MPEG CfE [25]) based on the perceptual quantization of HDR video content [31] and tone mapping-inverse tone mapping with metadata. The paper concludes that for specific bitrates, subjective evaluation results suggest that HDR video generated by the perceptual quantization scheme were rated higher than the videos reconstructed using the inverse tone-mapping scheme.…”

HDR video past, present and future: A perspective

“…Examples of one-stream HDR video compression include HDRv [23], adaptive LogLuv [24], PQ [25], HLG [26] and the Power Transfer Function method [27].…”

“…To satisfy manufacturers of both LED and OLED HDR displays, the UHD Alliance proposed two definitions of HDR There are currently three proposals to support consumer HDR in this first wave: HDR10 [12], HLG [26] and Dolby Vision [45]. HDR10 is based on a 10-bit PQ curve [25] which is part of SMPTE standard ST.2084 [12]. Television sets which support HDR10 are allowed by the UHD Alliance to use their Ultra HD Premium logo.…”

81‐4: Image Quality Evaluation of HDR Displays

“…To reproduce HDR contents, both HDR signal source and HDR display device are necessary. [1] The former provides the scene's real luminance information when capturing, and the latter uses a device independent electro-optical transfer function (EOTF), namely perceptual quantizer (PQ), to convert electric source signal to optical output signal, producing the same luminance as recorded in the HDR contents. Hanhart et al [2] compared HDR displays with SDR displays and pointed out that the former have obvious advantages over those with lower dynamic range.…”