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UT Arlington EE 5359 - AIC project proposal

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PROJECT REPORTTopic: Advanced Image CodingBy Radhika VeerlaUnder the guidance of Dr. K. R. RaoTABLE 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 extensionsHD-photo high-definition photo I-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 transformMSE mean square errorPGM portable graymapPNM portable any mapPPM portable pixel mapPSNR peak signal to noise ratioSSIM structural similarity index VLC variable length codingLIST OF FIGURESFigure 1 The process flow of the AIC encoder and decoder 2 YCbCr sampling formats - 4:4:4, 4:2:2 and 4:2:03 Different prediction modes used for prediction in AIC4 The specific coding parts of the profiles in H.2645 Basic coding structure for a macroblock in H.264/ AVC 6 Block diagram for CABAC7 Diagram for zig-zag scan and scan line order8 Block diagram of JPEG encoder and decoder9 Structure of JPEG 2000 codec10 Tiling, DC level shifting, color transformation, DWT of each image component11 Block diagram of JPEG-XR encoder and decoder12 JPEG-LS block diagram13 A causal template of LOCO-IImplementation 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, JPEG-XRObjective: It is proposed to implement advanced image coding (AIC) based on I-frame onlycoding using JM software and compare the results with other image compressiontechniques like JPEG, JPEG2000, JPEG-LS, JPEG-XR, Microsoft HD photo, H.263 I-frame coding. 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-framecoding, JPEG using baseline method, JPEG 2000 in non-scalable, but optimal mode.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]. H.264 technology aims to provide good videoquality at considerably low bit rates, at reasonable level of complexity while providingflexibility to wide range of applications [2]. Coding efficiency is further improved infidelity range extensions (FRExt) using 8x8 integer transform and works well for morecomplex visual content. JPEG [15] is first still image compression standard which uses8x8 block based DCT decomposition, while JPEG 2000 is a wavelet-based compressionstandard which has improved coding performance over JPEG with additional featureslike scalability and lossless coding capability has best performance with smooth spatialdata. JPEG performs well in low complexity applications whereas JPEG 2000 works wellin high complexity, lower bit-rate applications. JPEG2000 has rate-distortion advantageover JPEG. Microsoft HD photo [19] is a new still-image compression algorithm forcontinuous-tone photographic images which maintains highest image quality or deliversthe most optimal performance. JPEG-XR [16] (extended range), a standard for HD-photohas high dynamic-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 [30] (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. Transcoding converts H.263 compressionformat to that of H.264 and viceversa. If the transcoding is done in compression domain,it gives better results as the computation only needs to perform on compressed pixels.Although the above mentioned compression techniques are developed fordifferent signals, they work well for still image compression and hence worthwhile forcomparison. 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 [30] are used for comparison betweendifferent codecs. The evaluation will be done using bit rates, different quality assessmentmetrics like PSNR, SSIM and complexity.The following topics are discussed in this report. AIC is described in detail as it isimplemented and various other codecs used for comparison in brief. Different settingsused in the softwares and evaluation methodology are discussed. The results obtained byevaluating different test images and test images of different sizes using AIC referencesoftware are included. Advanced Image CodingAdvanced image coding (AIC) is a still image compression system which combines thealgorithms of H.264 and JPEG standard, shown in Fig.1, in order to achieve bestcompression capability in terms of quality factor with less complexity. The performanceof AIC is close to JPEG 2000 and is lot better than JPEG. AIC uses the intra-frame blockprediction, which is originally used in H.264 to reduce the large number of bits to codeoriginal input. Both AIC and H.264 use CABAC coding while AIC uses position ofcoefficient matrix as the context [1]. It is observed that each block in AIC is modified to get the best compression efficiencypossible.Fig.1: The process flow of the AIC encoder and decoder


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UT Arlington EE 5359 - AIC project proposal

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