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IMPLEMENTATION AND PERFOMANCE ANALYSIS OF H.264 INTRA FRAME CODING, JPEG, JPEG-LS , JPEG-2000 AND JPEG-XR. EE 5359 Multimedia Project Amee Solanki (1000740226 ) firstname.lastname@example.org. Image Compression. Compression is the process of compacting data, reducing the number of bits.
EE 5359 Multimedia Project
Amee Solanki (1000740226)email@example.com
Fig.1 Comparison of original coronary angiogram (left) with two compression results. Middle: JPEG data compression by factor of CR=12, Right: factor of CR=24.
There is no information loss, and the image can be reconstructed exactly the same as the original
Applications: medical imagery, archiving
Information loss is tolerable.
Applications: commercial distribution (DVD) and rate constrained environment where lossless methods cannot provide enough compression ratio
Fig.2 Evolution of compression technology
Table 1: Comparison of image compression standards
Fig.2 JPEG encoder block diagram 
Fig.3 JPEG decoder block diagram 
Fig. 4 (a) Encoder block diagram (b) Decoder block diagram of JPEG 2000 
Table 2: Comparison of JPEG and JPEG 2000 
Table 3: Comparison of JPEG-LS and JPEG-XR 
Fig.4 Examples of spatial intra prediction modes for (8X8) blocks 
Fig. 5 shows a 4x4 block containing 16 pixels labeled from a through p. A prediction block p is calculated based on the pixels labeled A-M obtained from the neighboring blocks.
Fig. 5 A 4X4 block and its neighboring pixels
Fig. 6 Direction of 9 4X4 intra-prediction 
Mode 0 is the vertical prediction mode in which pixels a, e, i, and m are predicted by A and so on.
Mode 1 is the horizontal prediction mode in which pixels a,b, c, and d are predicted by I and so on.
Mode 2 is called DC prediction in which all pixels i.e. (a to p) as shown in fig. 5 are predicted by (A+B+C+D+I+J+K+L)/8.
For modes 3-8, the predicted samples are formed from a weighted average of the prediction samples A-M.
Fig.8 H.264 Encoder and decoder block diagrams 
Criteria to evaluate a compressed image are as follows :
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
x and y correspond to two different signals that need to be compared, i.e. two different blocks in
two separate images ;
Fig. 9 SSIM Index example 
AVC advanced video coding
BMP bit map format
CABAC context adaptive binary arithmetic coding
DCT discrete cosine transform
EBCOT embedded block coding with optimized truncation
FRExt fidelity range extensions
GIF graphics interchange format
HD-photo high-definition photo
HVS human visual system
I-frame intra frame
JM joint model
JPEG joint photographic experts group
JPEG-LS joint photographic experts group lossless and lossless coding
JPEG-XR joint photographic experts group extended range
LBT lapped bi-orthogonal transform
LOCO-I low complexity lossless compression for images
MSE mean square error
PSNR peak signal to noise ratio
SSIM structural similarity index
VLC variable length coding
 JPEG Encoder and Decoder block diagram :http://www.cmlab.csie.ntu.edu.tw/cml/dsp/training/coding/jpeg/jpeg/decoder.htm
 JPEG2000 Encoder and Decoder block diagram :http://eeweb.poly.edu/~yao/EE3414/JPEG.pdf
 H.264 Encoder and Decoder block diagram : http://www.drtonygeorge.com/video_codec.htm
 SSIM Index example diagram:https://ece.uwaterloo.ca/~z70wang/research/ssim/
 H.264/AVC reference software (JM 17.2) website: http://iphome.hhi.de/suehring/tml/download/
 JPEG2000 latest reference software (Jasper Version 1.900.0) website: http://www.ece.uvic.ca/~mdadams/jasper/
 JPEG reference software website: ftp://ftp.simtel.net/pub/simtelnet/msdos/graphics/jpegsr6.zip
 JPEG-LS reference software website:http://www.hpl.hp.com/loco/
 T. Wiegand, G. J. Sullivan, G. Bjontegaard and A. Luthra,” Overview of the H.264 / AVC video coding standard ” IEEE Trans. on Circuits and Systems for Video Technology,vol. 13, pp. 560-576, July 2003.
 A.Skodras, C. Christopoulos and T. Ebrahimi, “The JPEG 2000 still image compression standard”, IEEE Trans. on Signal Processing, vol.18, pp. 36 - 58, Aug 2002.
 M. J. Weinberger, G. Seroussi and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS”, IEEE Trans. on Image Processing, vol.9, pp.1309-1324, Aug. 2000
 C. Christopoulos, A. Skodras and T.Ebrahimi, “The JPEG2000 still image coding system: an
overview”, IEEE Trans. on Consumer Electronics, vol.46, pp.1103-1127, Nov. 2000.
 T. Ebrahimi and M. Kunt, “ Visual data compression for multimedia applications”, Proc IEEE, vol.86, pp. 1109-1125, June 1998.
 Evolution of image compression standards :
 Intra-prediction modes image:
 Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. on Image Processing, vol. 13, no. 4, pp. 600-612, Apr. 2004.
 I. E. Richardson, “The H.264 advanced video compression standard”, II Edition, Wiley, 2010.
 D. S. Taubman and M. W. Marcellin, "JPEG2000 – Image compression fundamentals, standards, and practice," Kluwer, 2001.