Pipelines for HDR Video Coding Based on Luminance Independent Chromaticity Preprocessing

We consider the chromaticity in high dynamic range (HDR) video coding and show the advantages of a constant luminance color space for encoding. For this, we introduce two constant luminance HDR video coding pipelines, which convert the source video to linear $Y u^\prime v^\prime $ . A content dependent scaling of the chromaticity components serves as color quality parameter. This reduces perceivable color artifacts while remaining fully compatible with core High Efficiency Video Coding or other video coding standards. One of the pipelines further combines the scaling with a dedicated chromaticity transform to optimize the representation of the chromaticity components for encoding. We validate both pipelines with subjective user studies in addition to an objective comparison to the other state-of-the-art methods. The user studies show a significant improvement in perceived color quality at medium to high compression rates without sacrificing luminance quality compared with current standard coding pipelines. The objective evaluation suggests that both pipelines perform at least comparable to the current state-of-the-art methods.

[1]  Aljoscha Smolic,et al.  Art-directable Continuous Dynamic Range video , 2015, Comput. Graph..

[2]  Peng Yin,et al.  Adaptive reshaper for high dynamic range and wide color gamut video compression , 2016, Optical Engineering + Applications.

[3]  Touradj Ebrahimi,et al.  Subjective and objective evaluation of HDR video compression , 2015 .

[4]  Touradj Ebrahimi,et al.  Benchmarking of objective quality metrics for HDR image quality assessment , 2015, EURASIP Journal on Image and Video Processing.

[5]  Hans-Peter Seidel,et al.  Backward compatible high dynamic range MPEG video compression , 2006, SIGGRAPH 2006.

[6]  Changjun Li,et al.  The CIECAM02 Color Appearance Model , 2002, CIC.

[7]  Wilfried Philips,et al.  Evaluating color difference measures in images , 2016, 2016 Eighth International Conference on Quality of Multimedia Experience (QoMEX).

[8]  Jn Morovi,et al.  Color Gamut Mapping , 2008 .

[9]  Hans-Peter Seidel,et al.  Perception-motivated high dynamic range video encoding , 2004, SIGGRAPH 2004.

[10]  G. Bjontegaard,et al.  Calculation of Average PSNR Differences between RD-curves , 2001 .

[11]  Wolfgang Heidrich,et al.  HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions , 2011, SIGGRAPH 2011.

[12]  Panos Nasiopoulos,et al.  Compression of high dynamic range video using the HEVC and H.264/AVC standards , 2014, 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness.

[13]  Taoran Lu,et al.  ITP Colour Space and Its Compression Performance for High Dynamic Range and Wide Colour Gamut Video Distribution , 2016 .

[14]  Hans-Peter Seidel,et al.  Extending quality metrics to full luminance range images , 2008, Electronic Imaging.

[15]  Wolfgang Heidrich,et al.  Color correction for tone mapping , 2009, Comput. Graph. Forum.

[16]  Touradj Ebrahimi,et al.  Overview and evaluation of the JPEG XT HDR image compression standard , 2019, Journal of Real-Time Image Processing.

[17]  Patrick Le Callet,et al.  HDR-VQM: An objective quality measure for high dynamic range video , 2015, Signal Process. Image Commun..

[18]  Erik Reinhard,et al.  A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images , 2016, IEEE Computer Graphics and Applications.

[19]  Claire Mantel,et al.  Comparing subjective and objective quality assessment of HDR images compressed with JPEG-XT , 2014, 2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP).

[20]  Scott Miller,et al.  Perceptual Signal Coding for More Efficient Usage of Bit Codes , 2012 .

[21]  Touradj Ebrahimi,et al.  HDR image compression: A new challenge for objective quality metrics , 2014, 2014 Sixth International Workshop on Quality of Multimedia Experience (QoMEX).

[22]  Rafal Mantiuk,et al.  A high dynamic range video codec optimized by large-scale testing , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[23]  Tania Pouli,et al.  Evaluation of color encodings for high dynamic range pixels , 2015, Electronic Imaging.

[24]  M. Floater Mean value coordinates , 2003, Computer Aided Geometric Design.

[25]  Rafal Mantiuk,et al.  Display adaptive tone mapping , 2008, SIGGRAPH 2008.

[26]  Hans-Peter Seidel,et al.  High Dynamic Range Image and Video Compression - Fidelity Matching Human Visual Performance , 2007, 2007 IEEE International Conference on Image Processing.

[27]  Touradj Ebrahimi,et al.  ICtCp Versus Y'CbCr: Evaluation of ICtCp Color Space and an Adaptive Reshaper for HDR and WCG , 2018, IEEE Consumer Electronics Magazine.

[28]  Gregory Ward Larson,et al.  LogLuv Encoding for Full-Gamut, High-Dynamic Range Images , 1998, J. Graphics, GPU, & Game Tools.

[29]  Gary J. Sullivan,et al.  Overview of the High Efficiency Video Coding (HEVC) Standard , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[30]  Min H. Kim,et al.  Modeling human color perception under extended luminance levels , 2009, ACM Trans. Graph..

[31]  A. A. Clarke,et al.  Quantifying colour appearance. part IV. Transmissive media , 1993 .

[32]  Aljoscha Smolic,et al.  Luminance independent chromaticity preprocessing for HDR video coding , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[33]  Alan C. Bovik,et al.  A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms , 2006, IEEE Transactions on Image Processing.