EE 5359 FALL 2010 MULTIMEDIA PROCESSING PROJECT REPORT Performance Analysis and Comparison of H 264 Intraframe coding JPEG JPEG LS JPEG 2000 JPEG XR and AVS China Intraframe INSTRUCTOR DR K R RAO Shreyanka Subbarayappa Department of Electrical Engineering University of Texas at Arlington Email shreyanka subbarayappa mavs uta edu Page 1 List of acronyms AIC advanced image coding AVC advanced video coding AVS audio video standard BMP bit map format CABAC context adaptive binary arithmetic coding DCT discrete cosine transform DWT discrete wavelet transform EBCOT embedded block coding with optimized truncation EZW embedded zero tree wavelet coding FRExt fidelity range extensions HD photo high definition photo I frame intra frame IP intra prediction JM joint model JPEG joint photographic experts group JPEG LS joint photographic experts group lossless coding JPEG XR joint photographic experts group extended range LBT lapped bi orthogonal transform MSE mean square error PGM portable graymap PPM portable pixel map PSNR peak signal to noise ratio SSIM structural similarity index metric VLC variable length coding Page 2 LIST OF FIGURES Figure 1 Different prediction modes used for prediction in AIC and H 264 2 The specific coding parts of the profiles in H 264 3 Basic coding structure for H 264 AVC for a macroblock 4 Block diagram for CABAC 5 a Zig zag scan 5 b Scan line order 6 a Block diagram of JPEG encoder 6 b Block diagram of JPEG decoder 7 Structure of JPEG 2000 codec The structure of the a encoder b decoder 8 Tiling DC level shifting color transformation DWT of each image component 9 JPEG LS block diagram 10 Test sequences used 11 Structural similarity SSIM measurement system 12 Original and output decoded images LIST OF TABLES Table 1 Different parts of AVS 2 Different test sequences used Page 3 Performance Analysis and Comparison of H 264 Intraframe coding JPEG JPEG LS JPEG 2000 JPEG XR and AVS China Intraframe Abtract It is proposed to implement the H 264 intraframe coding using JM software 11 and compare the results with other image compression techniques like JPEG JPEG2000 JPEG LS JPEG XR and AVS China Part7 Coding simulations will be performed on various sets of test images Experimental results are to be measured in terms of bit rate quality PSNR SSIM etc This project considers only main and FRExt high profiles in H 264 AVC I frame coding JPEG using baseline profile JPEG 2000 in non scalable but optimal mode and AVS China part 7 Introduction H 264 technology aims to provide good video quality at considerably low bit rates at reasonable level of complexity while providing flexibility to wide range of applications 2 Coding efficiency is further improved in fidelity range extensions FRExt using 8x8 integer transform and works well for more complex visual content JPEG 5 is first still image compression standard which uses 8x8 block based DCT decomposition while JPEG 2000 is a wavelet based compression standard which has improved coding performance over JPEG with additional features like scalability and lossless coding capability has best performance with smooth spatial data 4 JPEG performs well in low complexity applications whereas JPEG 2000 works well in high complexity lower bit rate applications JPEG2000 has rate distortion advantage over JPEG Microsoft HD photo 10 is a new still image compression algorithm for continuous tone photographic images which maintains highest image quality or delivers the most optimal performance JPEG XR 10 extended range a standard for HD photo has high dynamic range image coding and performance as the most desirable feature Its performance is close to JPEG2000 with computational and memory requirement close to JPEG With half the file size of JPEG HD photo delivers lossy compressed image with better perceptual quality than JPEG and lossless compressed image at 2 5 times smaller than the original image JPEG LS 30 lossless is an ISO ITU T standard for lossless coding of still images In addition it also provides support for near lossless compression The main goal of JPEG LS has been to deliver a low complexity solution for lossless image coding with the best possible compression efficiency JPEG uses Huffman coding H 264 AVC and AIC systems adopts CABAC encoding technique and HD photo uses reversible integer integer mapping lapped bi orthogonal transform 7 LOCO I low complexity lossless compression for images an algorithm for JPEG LS uses adaptive prediction context modeling and Golomb coding 3 It supports near lossless compression by allowing a fixed maximum sample error Transcoding converts H 263 compression format to that of H 264 and viceversa Although the above mentioned compression techniques are developed for different signals they work well for still image compression and hence worthwhile for comparison Different softwares like JM software for H 264 11 JPEG reference software 7 for JPEG JasPer 8 for JPEG2000 HD photo reference software 10 JPEG LS reference software 9 and AVS Part7 software 28 are used for comparison Page 4 between different codecs The evaluation is carried out using bit rates different quality assessment metrics like PSNR SSIM 23 and complexity H 264 standard H 264 or MPEG 4 part 10 aims at coding video sequences at approximately half the bit rate compared to MPEG 2 at the same quality It also aims at having significant improvements in coding efficiency using CABAC entropy coder error robustness and network friendliness Parameter set concept arbitrary slice ordering flexible macroblock structure redundant pictures switched predictive and switched intra pictures have contributed to error resilience robustness of this standard Adaptive directional intra prediction Fig 1 is one of the factors which contributed to the high coding efficiency of this standard 2 Different modes used for block prediction are shown in Fig 1 Mode 0 Vertical Mode 1 Horizontal Mode 2 DC Mode 3 Diagonal Down Left Mode 4 Diagonal DownRight Page 5 Mode 5 Vertical Right Mode 6 Horizontal Down Mode 7 Vertical Left Mode 8 Horizontal Up Fig 1 Different prediction modes used for prediction in AIC and H 264 1 High Profiles Adaptive transform block size Quantization scaling matrices Extended Profile Main Profile CABAC Data partition B slice SI slice SP slice Weighted prediction I slice P slice CAVLC Arbitrary slice order Flexible macroblock order Redundant slice Baseline Profile Fig 2 The specific coding parts of the profiles in H 264 2 Page 6 Each profile
View Full Document
Unlocking...