Advanced Image Coding and its comparison with various codecs PROJECT REPORT Topic Advanced Image Coding By Radhika Veerla Supervising Professor Dr K R Rao Radhika Veerla Graduate Student UTA 1 Advanced Image Coding and its comparison with various codecs ACKNOWLEDGEMENT I would like to thank my advisor Dr K R Rao for all his guidance encouragement and support This work was enabled and sustained by his vision and ideas I am thankful to Dr Zhengbing Zhang for his constant support and advice given throughout this project Finally I would like to thank my lab members Att Vineeth and Pooja and also all the visiting professors for helping me resolving the issues and thus smooth completion of the project Radhika Veerla Graduate Student UTA 2 Advanced Image Coding and its comparison with various codecs TABLE OF ACRONYMS AIC advanced image coding AVC advanced video coding BMP bit map format CABAC DCT context adaptive binary arithmetic coding discrete cosine transform DWT discrete wavelet transform EBCOT embedded block coding with optimized truncation EZW embedded zero tree wavelet coding FRExt fidelity range extensions GIF graphics interchange format HD photo HVS high definition photo human visual perception I frame JM intra frame 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 LOCO I low complexity lossless compression for images MSE mean square error M AIC modified advanced image coding PGM portable gray map PNM portable any map PPM portable pixel map PSNR peak signal to noise ratio ROI region of interest SI switched intra SP switched predictive SSIM structural similarity index VLC variable length coding Radhika Veerla Graduate Student UTA 3 Advanced Image Coding and its comparison with various codecs LIST OF FIGURES Figure 1 The process flow of the AIC encoder and decoder 2 Color conversion matrices for RGB and YCbCr 3 YCbCr sampling formats 4 4 4 4 2 2 and 4 2 0 4 Different prediction modes used for prediction in AIC 5 M AIC encoder and decoder 6 The specific coding parts of the profiles in H 264 7 Basic coding structure for a macroblock in H 264 AVC 8 Block diagram for CABAC 9 Diagram for zig zag scan and scan line order 10 Block diagram of JPEG encoder and decoder 11 Structure of JPEG 2000 codec 12 Tiling DC level shifting color transformation DWT of each image component 13 Block diagram of JPEG XR encoder and decoder 14 JPEG LS block diagram 15 A causal template of LOCO I 16 Structural similarity SSIM measurement system Radhika Veerla Graduate Student UTA 4 Advanced Image Coding and its comparison with various codecs Implementation of AIC based on I frame only coding in H 264 and comparison with other still frame image coding standards such as JPEG JPEG 2000 JPEG LS and JPEG XR Objective Advanced image coding AIC is implemented based on I frame only coding using Microsoft Visual C and results are compared with other image compression techniques like JPEG JPEG2000 JPEG LS JPEG XR and H 264 Coding simulations are performed on various sets of test images Experimental results are measured in terms of bit rate quality PSNR This project considers only main and FRExt high profiles in H 264 AVC I frame coding JPEG using baseline method and all the codecs are considered in lossy compression Introduction The aim of AIC 1 is to provide better quality with reduced level of complexity while optimizing readability and clarity Though its aim is not to optimize speed it is faster than many of the JPEG 2000 codecs 10 Because of its high quality images the applications of AIC include medical imaging 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 15 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 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 19 is a new still image compression algorithm for continuous tone photographic images and it maintains highest image quality or delivers the most optimal performance JPEG XR 16 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 requirements 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 25 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 is 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 adopt 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 It supports near lossless compression by allowing a fixed maximum sample error Although the above mentioned compression techniques are developed for different signals they work well for still image compression and hence worthwhile for Radhika Veerla Graduate Student UTA 5 Advanced Image Coding and its comparison with various codecs comparison Different softwares like AIC reference software JM software for H 264 17 JPEG reference software 18 for JPEG HD photo reference software 19 JasPer 20 for JPEG2000 JPEG LS reference software 21 are used for comparison between different codecs The evaluation will be done using bit rates different quality assessment metrics like PSNR SSIM and complexity The following topics are discussed in this report AIC is described in detail as it is implemented
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