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UT Arlington EE 5359 - Advanced Image Coding

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Advanced Image Coding and its comparison with various codecsPROJECT REPORTTopic: Advanced Image CodingBy Radhika VeerlaSupervising Professor: Dr. K. R. RaoRadhika Veerla, Graduate Student, UTA1Advanced Image Coding and its comparison with various codecsACKNOWLEDGEMENTI would like to thank my advisor, Dr.K.R.Rao, for all his guidance, encouragement andsupport. This work was enabled and sustained by his vision and ideas. I am thankful to Dr. Zhengbing Zhang for his constant support and advice giventhroughout this project. Finally, I would like to thank my lab members Att, Vineeth and Pooja and also all thevisiting professors for helping me resolving the issues and thus smooth completion of theproject.Radhika Veerla, Graduate Student, UTA2Advanced Image Coding and its comparison with various codecsTABLE OF ACRONYMSAIC advanced image codingAVC advanced video codingBMP bit map formatCABAC context adaptive binary arithmetic codingDCT discrete cosine transformDWT discrete wavelet transformEBCOT embedded block coding with optimized truncationEZW embedded zero-tree wavelet coding FRExt fidelity range extensionsGIF graphics interchange formatHD-photo high-definition photoHVS human visual perceptionI-frame intra frameJM joint modelJPEG joint photographic experts groupJPEG-LS joint photographic experts group lossless codingJPEG-XR joint photographic experts group extended rangeLBT lapped bi-orthogonal transformLOCO-I low complexity lossless compression for imagesMSE mean square errorM-AIC modified advanced image codingPGM portable gray mapPNM portable any mapPPM portable pixel mapPSNR peak signal to noise ratioROI region of interestSI switched intraSP switched predictiveSSIM structural similarity index VLC variable length codingRadhika Veerla, Graduate Student, UTA3Advanced Image Coding and its comparison with various codecsLIST OF FIGURESFigure 1 The process flow of the AIC encoder and decoder 2 Color conversion matrices for RGB and YCbCr3 YCbCr sampling formats - 4:4:4, 4:2:2 and 4:2:04 Different prediction modes used for prediction in AIC5 M-AIC encoder and decoder6 The specific coding parts of the profiles in H.2647 Basic coding structure for a macroblock in H.264/ AVC 8 Block diagram for CABAC9 Diagram for zig-zag scan and scan line order10 Block diagram of JPEG encoder and decoder11 Structure of JPEG 2000 codec12 Tiling, DC level shifting, color transformation, DWT of each image component13 Block diagram of JPEG-XR encoder and decoder14 JPEG-LS block diagram15 A causal template of LOCO-I16 Structural similarity (SSIM) measurement systemRadhika Veerla, Graduate Student, UTA4Advanced Image Coding and its comparison with various codecsImplementation of AIC based on I-frame only coding in H.264and comparison with other still frame image coding standardssuch as JPEG, JPEG 2000, JPEG-LS and JPEG-XRObjective: Advanced image coding (AIC) is implemented based on I-frame only coding usingMicrosoft Visual C++ and results are compared with other image compression techniqueslike JPEG, JPEG2000, JPEG-LS, JPEG-XR and H.264. Coding simulations areperformed on various sets of test images. Experimental results are measured in terms ofbit-rate, quality- PSNR. This project considers only main and (FRExt) high profiles inH.264/AVC I-frame coding, JPEG using baseline method and all the codecs areconsidered in lossy compression.Introduction: The aim of AIC [1] is to provide better quality with reduced level of complexity whileoptimizing readability and clarity. Though its aim is not to optimize speed, it is faster thanmany of the JPEG 2000 codecs [10]. Because of its high quality images, the applicationsof AIC include medical imaging. H.264 technology aims to provide good video quality atconsiderably low bit rates, at reasonable level of complexity while providing flexibility towide range of applications [2]. Coding efficiency is further improved in fidelity rangeextensions (FRExt) using 8x8 integer transform and works well for more complex visualcontent. JPEG [15] is first still image compression standard which uses 8x8 block basedDCT decomposition, while JPEG 2000 is a wavelet-based compression standard whichhas improved coding performance over JPEG with additional features like scalability andlossless coding capability has best performance with smooth spatial data. JPEG performswell 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-tonephotographic images and it maintains highest image quality or delivers the most optimalperformance. JPEG-XR [16] (extended range), a standard for HD-photo has highdynamic-range image coding and performance as the most desirable feature. Itsperformance is close to JPEG2000 with computational and memory requirements close toJPEG. With half the file size of JPEG, HD photo delivers lossy compressed image withbetter perceptual quality than JPEG and lossless compressed image at 2.5 times smallerthan the original image. JPEG-LS [25] (lossless) is an ISO/ITU-T standard for losslesscoding 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 forlossless image coding with the best possible compression efficiency. JPEG uses Huffmancoding, H.264/AVC and AIC systems adopt CABAC encoding technique, and HD photouses reversible integer-integer-mapping lapped bi-orthogonal transform [7]. LOCO-I (lowcomplexity lossless compression for images), an algorithm for JPEG-LS uses adaptiveprediction, context modeling and Golomb coding. It supports near lossless compressionby allowing a fixed maximum sample error. Although the above mentioned compression techniques are developed for differentsignals, they work well for still image compression and hence worthwhile forRadhika Veerla, Graduate Student, UTA5Advanced Image Coding and its comparison with various codecscomparison. 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


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UT Arlington EE 5359 - Advanced Image Coding

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