I. INTRODUCTIONII. OVERVIEW OF H.264III. Fidelity RANGE EXTENSIONSIV. YCgCo Color SpaceV. Residual Color Transform (RCT)VI. Proposed Algorithm And ResultsVII. Key Technical AreaVIII. ConclusionsIX. Future WorkAbstract—In today’s world, professional videoapplications, demanding very high video quality, aregaining a lot of attention, from both academia andindustry. These professional video applications are high-definition TV/DVD, high quality cinema, video postprocessing algorithms, studio editing, content distributionand many others. All these applications demand a veryhigh-quality video. Along with achieving video of thehighest quality, it is essential to focus on the codingefficiency. This research aims at addressing these real-lifeneeds. This research implements lossless coding of video in4:4:4 sampling format. This guarantees a high-fidelity atthe output. In order to achieve a high coding gain, the red,green and blue (RGB) components of a video signal aredecorrelated by transforming them into the newly-defined‘YCgCo’ color space [27]. YCgCo color space wasintroduced in the Fidelity Range Extensions (FRExts)amendment [4] of H.264/MPEG-4 part 10 Advanced VideoCoding standard [1]. Another important conceptimplemented as a part of this research is the residual colortransform (RCT) [9]. RCT was introduced in the High4:4:4 profile of the FRExts. Index Terms— H.264/MPEG-4 part 10 AVC, losslesscoding, residual color transform, YCgCo color spaceI. INTRODUCTIONvideo signal is represented using three components –one luminance and two chrominance or color differencecomponents. The human visual system is less sensitive to thechrominance components as compared to the luminancecomponent. Hence, the chrominance samples can berepresented at a lower resolution than the luminance samples.This technique is called the chroma subsampling technique[20]. Its advantage is that it leads to high compression at thecost of introducing an insignificant distortion in the videooutput. However, for professional video applications, thisdistortion is not acceptable [8]. Hence, the video processing isperformed in the 4:4:4 sampling format. In this format, allthe components are represented at equal resolution. Due toincreasing demand for usage of 4:4:4 sample space, there isalso a need for efficient coding tools in this space. Losslesscoding is implemented to address the high video qualitydemand. The lossless coding coupled with 4:4:4 sample spaceleads to high volumes of data. Achieving a good compressionratio along with good coding efficiency is the motivation ofthis research. This research aims at implementing analgorithm to achieve lossless coding for YUV 4:4:4Asequences. High definition sequences [19] are used in thisresearch to address the needs of the professional applications.The proposed algorithm implements the conversion of YCbCrto RGB. The inter-prediction is performed in the RGBdomain. The residual signals obtained are transformed toYCgCo color space [7]. These transformed signals are thenencoded using arithmetic coding. The stage of quantization isbypassed in the implemented algorithm to account for losslesscoding. The size of the encoded bitstream is measured and thecompression ratio is calculated. The coefficients are thenreverse transformed to the RGB domain to obtain the residualsignals in the RGB domain. The reference frame is added tothe residual frame to reconstruct the original frame. Theoutput frame is displayed and the error frame is calculated.The quality of the reconstructed frame is measured using themetrics of mean square error and peak-signal-to-noise ratio. II. OVERVIEW OF H.264 H.264/MPEG-4 part 10 AVC is one of the latest videocoding standards introduced in the world of videocompression [1]. It was developed by the Joint Video Team(JVT), consisting of VCEG (Video Coding Experts Group) ofITU-T (International Telecommunication Union –Telecommunication standardization sector) and MPEG(Moving Picture Experts Group) of ISO/IEC [1]. Thisstandard is noted for enhanced compression efficiency. It cansupport various interactive (video telephony) and non-interactive (broadcast, streaming, storage, video on demand)applications, as it facilitates a network friendly videorepresentation [2]. The previous coding standards of MPEG-1, MPEG-2, MPEG-4 part2, H.261, H.262 and H.263 [1] [31]are the basis on which the H.264 is developed. It uses thebasic principles of transform for reduction of spatialcorrelation, quantization for control of bitrate, motioncompensated prediction for reduction of temporal correlation,and entropy coding for reduction in statistical correlation.The improved coding efficiency of H.264 has resulted due tochanges in the functional elements by including the followingenhancements: Adaptive intra-picture prediction Small block size transform with integer precision Multiple reference pictures and generalized B-pictures Variable block sizes Quarter pel precision for motion compensation Content adaptive in-loop deblocking filter Improved entropy coding by introduction of CABAC(context adaptive binary arithmetic coding) and CAVLC(context adaptive variable length coding) Implementation and evaluation of residual colortransform for 4:4:4 lossless RGB codingPooja V. Agawane and K. R. Rao, Fellow, IEEE Electrical Engineering Department,University of Texas at Arlington, Arlington, Texas1However, with the increase in the coding efficiency, there isan increase in the complexity to the encoder and the decoderof H.264. To reduce the implementation complexity, severaltechniques, like multiplier free integer transform, are used. Inorder to develop error resilience for transmission ofinformation over the networks, H.264 supports the methods offlexible macroblock ordering, switched slice, arbitrary sliceorder, redundant slice, data partitioning and parametersetting.H.264/AVC standard is comprised of a wide range
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