Skip to Main content Skip to Navigation
Journal articles

An Adaptive Quantizer for High Dynamic Range Content: Application to Video Coding

Abstract : In this paper, we propose an adaptive perceptual quantization method to convert the representation of High Dynamic Range (HDR) content from the floating point data type to integer, which is compatible with the current image/video coding and display systems. The proposed method considers the luminance distribution of the HDR content, as well as the detectable contrast threshold of the Human Visual System (HVS), in order to preserve more contrast information than the Perceptual Quantizer (PQ) in integer representation. Aiming to demonstrate the effectiveness of this quantizer for HDR video compression, we implemented it in a mapping function on the top of the HDR video coding system based on High Efficiency Video Coding (HEVC) standard. Moreover, a comparison function is also introduced to decrease the additional bit-rate of side information, generated by the mapping function. Objective quality measurements and subjective tests have been conducted in order to evaluate the quality of the reconstructed HDR videos. Subjective test results have shown that the proposed method can improve, in a significant manner, the perceived quality of some reconstructed HDR videos. In the objective assessment, the proposed method achieves improvements over PQ in term of the average bit-rate gain for metrics used in the measurement.
Complete list of metadatas

Cited literature [46 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01704278
Contributor : Giuseppe Valenzise <>
Submitted on : Thursday, March 5, 2020 - 11:35:21 AM
Last modification on : Tuesday, April 28, 2020 - 6:23:53 PM

File

Yi_TIP2017.pdf
Files produced by the author(s)

Identifiers

Citation

Yi Liu, Naty Sidaty, Wassim Hamidouche, Olivier Deforges, Giuseppe Valenzise, et al.. An Adaptive Quantizer for High Dynamic Range Content: Application to Video Coding. IEEE Transactions on Circuits and Systems for Video Technology, Institute of Electrical and Electronics Engineers, 2019, 29 (2), pp.531-545. ⟨10.1109/TCSVT.2017.2786746⟩. ⟨hal-01704278⟩

Share

Metrics

Record views

394

Files downloads

118