Implementation of AIC based on Iframe only coding in H'264 and comparison with other still frame ima

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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, JPEG-XR
Presentation for Ambrado Inc. Richardson, Texas,
on June 13, 2008

• Radhika Veerla
• radhika.veerla_at_uta.edu
• EE Graduate student,
• UT Arlington

MULTIMEDIA PROCESSING LAB

ELECTRICAL ENGINEERING
DEPARTMENT, THE UNIVERSITY OF TEXAS AT ARLINGTON
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Advanced Image Coding Block Diagram
(a) Encoder 1
(b) Decoder 1
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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 transmitted in scan-line order
• Makes use of CABAC similar to H.264 with several
  contexts

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Proposed AIC Algorithm
(a) Proposed AIC Encoder
(b) Proposed 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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H.264 Block Diagram
2
6

• H.264 Main Profile Intra-Frame Coding
• Transform block size reduced from 8x8 to 4x4
• H.264 relies on spatial prediction taking the
  advantage of inter-block spatial correlation
• Uses multiplier-less integer transforms and
  implemented in 16-bit fixed point architectures
• Block DCT with inter-block correlation is
  competitive with global wavelet coding used in
  JPEG2000
• Use CABAC or CAVLC
• H.264 High Profile Intra-Frame Coding
• H.264 Fidelity range extensions support
  higher-resolution color spaces
• Advantage- improves coding efficiency by adding
  8x8 integer transform, prediction schemes
  associated with adaptive selection between 4x4
  and 8x8 transforms

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JPEG Encoder and Decoder
(a) Encoder 6
(b) Decoder 6
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• JPEG-Baseline
• 8x8 block based DCT
• Scalar quantization
• Different quantization tables for luminance and
  chrominance components
• Huffman coding
• JPEG2000
• Relies on wavelet transform
• EBCOT scheme for coding wavelet coefficients
• Adaptive context-based binary arithmetic coding
• This project disables tiling and scalable mode
  for comparison as they adversely affect
  rate-distortion performance

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Evaluation MethodologySoftwares and parameters
used for comparison

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Codec Settings

• H.264
• Main and high profiles in 420 coding mode
• Activate intra coding profile for Frext
• Activate RGB coding mode
• 8x8 transform mode enabled, allowing adaptive
  choice between (4x4) /(8x8) transform and all
  associated prediction modes
• Motion estimation enabled
• CABAC enabled
• R-D optimization enabled
• De-blocking filter enabled
• HD photo
• No tiling
• One-level of overlap in the transformation stage
• No color space sub-sampling
• Spatial bit-stream order
• All sub-bands are included without any skipping

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Image Quality Measures

• Criteria to evaluate compression quality
• Two types of quality measures
• Objective quality measure- PSNR, MSE
• Structural quality measure- SSIM
• MSE and PSNR for a NxM pixel image are defined as
• where x is the original image and y is the
  reconstructed image. M and N are the width and
  height of an image and L is the maximum pixel
  value in the NxM pixel image.

(1)
(2)
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Structural Similarity Method

• This method emphasizes that the Human Visual
  System (HVS) is highly adapted to extract
  structural information from visual scenes.
  Therefore, structural similarity measurement
  should provide a good approximation to perceptual
  image quality.
• The SSIM index is defined as a product of
  luminance, contrast and structural comparison
  functions. 14

where µ is the mean intensity, and s is the
standard deviation as a round estimate of the
signal contrast. C1 and C2 are constants. M is
the numbers of samples in the quality map.
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Results for same resolutions
(a) Lena (512x512x24)
(b) Airplane (512x512x24)
(c) Peppers (512x512x24)
(d) Sailboat (512x512x24)
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Results (contd.)
(e) Splash (512x512x24)
(f) Couple (256x256x24)
(g) Cameraman (256x256x8)
(h) Man (256x256x8)
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Results for different resolutions (contd.)
(i) Lena (32x32x24)
(j) Lena (64x64x24)
(l) Lena (256x256x24)
(k) Lena (128x128x24)
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Conclusions and Future Work

• AIC outperforms JPEG by about 5dB and performs
  similar to or surpasses the JPEG2000 performance
  below 2bpp.
• Typical bit rates for AIC are 0-2bpp for color
  images and 0-4bpp for gray scale images
• H.264 outperforms every other codec for images of
  all resolutions, but works close to other codecs
  in case of gray-scale images. The main concern is
  its complexity.
• For gray scale images, all the codecs including
  H.264 have similar performance.
• The gap between various standards increases with
  decrease in image resolutions.
• The limitation of JPEG reference software is that
  it has low dynamic range.
• AIC is preferred because of its optimal
  performance with reduced complexity and increased
  speed.
• Comparison with JPEG-LS and JPEG-XR and also
  including SSIM distortion measurement in
  Rate-Distortion curves (PSNR and SSIM vs bpp) can
  be the future work.

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References

• 1 AIC website http//www.bilsen.com/aic/
• 2 T. Wiegand, G. Sullivan, G. Bjontegaard and
  A. Luthra, Overview of the H.264/AVC Video
  Coding Standard, IEEE Transactions on Circuits
  and Systems for Video Technology, vol. 13,
  pp.560-576, July 2003
• 3 P. Topiwala, Comparative study of JPEG2000
  and H.264/AVC FRExt I-frame coding on high
  definition video sequences, Proc. SPIE Intl
  Symposium, Digital Image Processing, San Diego,
  Aug. 2005.
• 4 P. Topiwala, T. Tran and W.Dai, Performance
  comparison of JPEG2000 and H.264/AVC high profile
  intra-frame coding on HD video sequences, Proc.
  SPIE Intl Symposium, Digital Image Processing,
  San Diego, Aug. 2006.
• 5 T.Tran, L.Liu and P. Topiwala, Performance
  comparison of leading image codecs H.264/AVC
  intra, JPEG 2000, and Microsoft HD photo, Proc.
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• 6 G. K. Wallace, The JPEG still picture
  compression standard, Communication of the ACM,
  vol. 34, pp. 31-44, April 1991.
• 7 H.264/AVC reference software (JM 12.2)
  Website http//iphome.hhi.de/suehring/tml/downloa
  d/
• 8 JPEG reference software Website
  ftp//ftp.simtel.net/pub/simtelnet/msdos/graphics/
  jpegsr6.zip
• 9 JPEG2000 latest reference software (Jasper
  Version 1.900.0) Website http//www.ece.ubc.ca/md
  adams/jasper
• 10 Microsoft HD photo specification
  http//www.microsoft.com/whdc/xps/wmphotoeula.mspx
  
• 11 D. Marpe, V. George, and T.Weigand,
  Performance comparison of intra-only H.264/AVC
  HP and JPEG 2000 for a set of monochrome ISO/IEC
  test images, JVT-M014, pp.18-22, Oct. 2004.
• 12 M.J. Weinberger, G. Seroussi and G. Sapiro,
  The LOCO-I lossless image compression algorithm
  principles and standardization into JPEG-LS,
  IEEE Trans. Image Processing, vol. 9, pp.
  1309-1324, Aug.2000.http//www.hpl.hp.com/loco/
• 13 G. J. Sullivan, ISO/IEC 29199-2 (JpegDI
  part 2 JPEG XR image coding Specification),
  ISO/IEC JTC 1/SC 29/WG1 N 4492, Dec 2007
• 14 Z. Wang and A. C. Bovik, Image quality
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  13, pp. 600 612, Apr. 2004.