Modified advanced image coding Zhengbing Zhang Electronics and Information College Yangtze University Supervisor Dr K R Rao Electrical Engineering Department University of Texas at Arlington Outline 1 Introduction 2 JPEG Baseline 3 JPEG 2000 4 Advanced Image Coding 5 Modified Advance Image Coding M AIC 6 Simulations 7 Conclusions and Future Work 1 Introduction JPEG 1 has played an important role in image storage and transmission since its development JPEG provides very good quality of reconstructed images at low or medium compression but it suffers from blocking artifacts at high compression Several papers 2 7 have been published to improve the performance of DCT based image compression In his website 8 Bilsen provides an experimental still image compression system known as Advanced Image Coding AIC that performs much better than JPEG and close to JPEG 2000 10 2 JPEG Baseline a Encoder b Decoder 3 JPEG 2000 Based on wavelet transform Context Coding Algorithm EBCOT Embedded Block Coding with Optimal Truncation Context based Arithmetic Entropy Coding This simulation disables tiling and scalable mode Reference software 10 JasPer v 1 900 1 4 Advanced Image Coding a Encoder 8 b Decoder 8 Advanced Image Coding It is a still image compression system which is a combination of H 264 and JPEG standards Features No sub sampling higher quality compression ratios 9 prediction modes as in H 264 Predicted blocks are predicted from previously decoded blocks Uses DCT to transform 8x8 residual block instead of transform coefficients as in JPEG Employs uniform quantization Uses floating point algorithm Coefficients encoded in scan line order Makes use of CABAC similar to H 264 with several contexts 5 M AIC R G Cr Cb Y Cb Cr Blks Y B CC Res Q FDCT mode Block Predict DecY DecCb DecCr Dec Y Pred Blk Y Mode Select and Store ZZ Table Predictor Res IDCT Huff A A C Q 1 ModeEnc a M AIC Encoder B G R ICC Cr Cb Y Cb Cr Blks Res IDCT Y Pred Blk DecY DecCb DecCr Q 1 Block Predict IZZ IHuff Table mode A A D ModeDec and Store b M AIC Decoder CC color conversion ICC Inverse CC ZZ zig zag scan IZZ inverse ZZ AAC adaptive arithmetic coder AAD AA decoder Color Conversion Y 0 299R 0 587G 0 114B Cb 0 169 R 0 331G 0 5 B Cr 0 5 R 0 419G 0 081 B R Y 1 402Cr G Y 0 344Cb 0 714Cr B Y 1 772Cb YCbCr format is 4 4 4 The color conversion method same as in JPEG reference software 9 is used Prediction Modes 8 Mode 0 Vertical Mode 1 Horizontal Mode 3 Diagonal Down Left Mode 4 Diagonal Down Right Mode 6 Horizontal Down Mode 7 Vertical Left Mode 2 DC Mode 5 Vertical Right Mode 8 Horizontal Up Prediction Modes contd Determine only when coding each Y block By full search among the 9 modes minimize the prediction error with Sum of Absolute Difference The selected prediction mode is stored used for blocks in Y Cb and Cr ModeEnc encodes selected prediction modes with a variable length algorithm Encode the prediction residual The prediction residual Res is transformed into DCT coefficients with floating point DCT DCT coefficients are uniformly scalar quantized same QP for all the DCT coefficients of Y Cb and Cr zig zag scan Encode 64 coefficients of a block with the same algorithm for the AC coefficients in JPEG 1 9 Use the Huffman table for AC coefficients of chrominances recommended in baseline JPEG 1 9 File Format stream header 11 bytes format flag version QP image width image height pixel depth code size of the compressed modes stream order header code of prediction modes Huffman codes of Y Res Cb Res and Cr Res An adaptive arithmetic coder 12 13 input byte by byte from the compressed stream output finally compressed result M AIC Codec M AIC Codec 6 Simulations Performance comparisons with bit rate vs PSNR Original and compressed Lena image with different methods Test images a Lena 512 512 24 b Airplane 512 512 24 c Couple 256 256 24 d Peppers 512 512 24 e Splash 512 512 24 f Sailboat 512 512 24 Performance comparisons with bit rate vs PSNR 38 40 36 34 35 30 PSNR dB PSNR dB 32 28 26 24 AIC M AIC JPEG Ref JPEG2000 22 20 18 0 0 2 0 4 0 6 0 8 Bits Per Pixel 1 1 2 25 AIC M AIC JPEG Ref JPEG2000 20 15 1 4 a Lena 512x512x24 36 30 0 0 5 1 1 5 Bits Per Pixel 2 2 5 b Airplane 512x512x24 35 34 30 32 28 PSNR dB PSNR dB 30 26 25 20 24 AIC M AIC JPEG Ref JPEG2000 22 20 18 0 0 2 0 4 0 6 0 8 Bits Per Pixel c Couple 256x256x24 1 1 2 AIC M AIC JPEG Ref JPEG2000 15 1 4 10 0 0 2 0 4 0 6 0 8 1 Bits Per Pixel 1 2 1 4 d Peppers 512x512x24 1 6 1 8 Performance comparisons with bit rate vs PSNR contd 45 32 30 40 28 26 30 PSNR dB PSNR dB 35 25 22 20 20 AIC M AIC JPEG Ref JPEG2000 15 10 24 0 0 5 1 1 5 2 2 5 Bits Per Pixel e Splash 512x512x24 3 3 5 AIC M AIC JPEG Ref JPEG2000 18 16 4 14 0 0 2 0 4 0 6 0 8 1 Bits Per Pixel 1 2 1 4 f Sailboat 512x512x24 1 6 1 8 Original and compressed Lena image with different methods a Original Lena 512 512 24 b AIC 0 22bpp PSNR 28 84dB c JPEG2000 0 22bpp PSNR 29 57dB Compressed Lena image with different methods contd d M AIC 0 22bpp PSNR 29 02dB e JPEG 0 22bpp PSNR 24 29dB Compressed Lena image with different methods contd f AIC 0 15bpp PSNR 27 29dB g M AIC 0 15bpp PSNR 27 43dB h JPEG 0 16bpp PSNR 14 05dB Conclusions and Future Work M AIC performs much better than baseline JPEG close to AIC and JPEG 2000 and a little bit better than AIC at some low bit rate range Replace the Huffman coder and AAC with CABAC Replace floating point DCT with integer DCT Try more prediction modes References 1 2 3 4 5 6 7 8 9 10 11 12 13 14 W B Pennebaker and J L Mitchell JPEG still image data compression standard Van Nostrand Reinhold New York 1993 A Gupta et al Modified runlength coding for improved JPEG performance Intl Conf on Information and Communication Technology 2007 pp 235 237 Dhaka Bangladesh March 2007 G Lakhani DCT coefficient prediction for JPEG image coding IEEE Int Conf Image Processing 2007 vol 4 pp IV 189 IV 192 Oct 2007 C Wang et al An improved JPEG compression algorithm based on sloped facet model of image segmentation Intl Conf on Wireless Communications Networking and Mobile Computing 2007 WiCom 2007 pp 2893 2896 Sept 2007 K Lee D S Kim and T Kim Regression based …
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