Modified advanced image coding

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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
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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

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1. Introduction

• JPEG1 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 27 have been published to
  improve the performance of DCT-based image
  compression.
• In his website8, Bilsen provides an
  experimental still image compression system known
  as Advanced Image Coding (AIC) that performs much
  better than JPEG and close to JPEG-200010.

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2. JPEG-Baseline
(a) Encoder
(b) Decoder
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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 software10 JasPer v 1.900.1

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4. Advanced Image Coding
(a) Encoder 8
(b) Decoder 8
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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

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5. M-AIC
(a) M-AIC Encoder
(b) M-AIC Decoder
CC - color conversion, ICC - Inverse CC, ZZ
zig-zag scan, IZZ inverse ZZ, AAC adaptive
arithmetic coder, AAD AA decoder.
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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
• RY 1.402Cr
• GY - 0.344Cb-0.714Cr
• BY 1.772Cb
• YCbCr format is 444.
• The color conversion method same as in JPEG
  reference software 9 is used.

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Prediction Modes8
Mode 0 Vertical
Mode 1 Horizontal
Mode 2 DC
Mode 3 Diagonal Down-Left
Mode 4 Diagonal Down-Right
Mode 5 Vertical-Right
Mode 6 Horizontal-Down
Mode 7 Vertical-Left
Mode 8 Horizontal-Up
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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.

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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 JPEG19.
• Use the Huffman table for AC coefficients of
  chrominances recommended in baseline JPEG 19.
  

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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 1213 input
  byte-by-byte from the compressed stream output
  finally compressed result.

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M-AIC Codec
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M-AIC Codec
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6. Simulations

• Performance comparisons with bit-rate vs PSNR
• Original and compressed Lena image with different
  methods

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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
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Performance comparisons with bit-rate vs PSNR
(a) Lena (512x512x24)
(b) Airplane (512x512x24)
(c) Couple (256x256x24)
(d) Peppers (512x512x24)
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Performance comparisons with bit-rate vs
PSNR(contd.)
(e) Splash (512x512x24)
(f) Sailboat (512x512x24)
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Original and compressed Lena image with different
methods

• Original Lena
• (512?512?24)

(b) AIC 0.22bpp, PSNR28.84dB
(c) JPEG2000 0.22bpp, PSNR29.57dB

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Compressed Lena image with different
methods(contd.)
(d) M-AIC 0.22bpp, PSNR29.02dB
(e) JPEG 0.22bpp, PSNR24.29dB
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Compressed Lena image with different
methods(contd.)
(f) AIC 0.15bpp, PSNR27.29dB
(g) M-AIC 0.15bpp, PSNR27.43dB
(h) JPEG 0.16bpp, PSNR14.05dB
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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

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References

• 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
  prediction for blocking artifact reduction in
  JPEG-compressed images, IEEE Trans. Image
  Processing, Vol. 14, pp. 36 48, Jan. 2005.
• E. Yang and L. Wang, Joint optimization of
  run-length coding, Huffman coding and
  quantization table with complete baseline JPEG
  compatibility, IEEE Int. Conf. Image Processing,
  2007, vol. 3, pp.III-181 III-184, Oct. 2007.
• J. Huang and S. Liu, Block predictive transform
  coding of still images, in Proc. IEEE ICASSP-94,
  vol. 5, pp.III-181 III-184, April 1994.
• AIC website http//www.bilsen.com/aic/
• JPEG reference software website
  ftp//ftp.simtel.net/pub/simtelnet/msdos/graphics/
  jpegsr6.zip
• JPEG 2000 reference software JasPer version
  1.900.1 on website http//www.ece.uvic.ca/mdada
  ms/jasper/
• J. Ostermann et al., Video coding with
  H.264/AVC tools, performance, and complexity,
  IEEE Circuits and Systems Magazine, vol. 4, issue
  1, pp. 7-28, first quarter 2004.
• I. H. Witten, R. M. Neal, and J. G. Cleary,
  Arithmetic coding for data compression,
  Communications of the ACM, vol. 30, pp. 520-540,
  June 1987.
• Adaptive arithmetic coding source code
  http//www.cipr.rpi.edu/wheeler/ac/
• Y-W. Chang and Y-Y. Chen, Novel artifact removal
  algorithm in the discreste cosine transform
  domain, JEI, vol. 17, pp.013012-1013012-12,
  Jan.-Mar. 2008.

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Thank you !