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Medical image compression

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Project Presentation presented in the final semester of B.Tech (EEE) during the session of 2010-11 By Paras Prateek Bhatnagar, Paramjeet Singh Jamwal, Nisha Rajani & Preeti Kumari.

Project Presentation presented in the final semester of B.Tech (EEE) during the session of 2010-11 By Paras Prateek Bhatnagar, Paramjeet Singh Jamwal, Nisha Rajani & Preeti Kumari.

Published in: Technology, Art & Photos

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  • 1. COMPRESSION PREPARED BY:UNDERGUIDANCE NISHA RAJANI (01)OF : PARAMJEET SINGH JAMWAL (07) PARAS PRATEEK BHATNAGARMr. A. S. YADAV (08)Mr. A. SHUKLA PREETI KUMARI (12)
  • 2. Contents …Why We Opted For This Project & Our Aim ?What is IMAGE COMPRESSION & Its Benefits ?MEDICAL IMAGE COMPRESSION & Differences .What is JPEG Compression?Our Results of IMAGE COMPRESSION Using DCT .Tasks Left In Our Project .Applications of MEDICAL IMAGE COMPRESSION .
  • 3. Why we Opted For This Project ?Shortcomings of present IMAGE COMPRESSION methods : A large bandwidth is required for transmission . A large time is required for compression .Lack of perfect lossless method which could preserve dataOur Aim .Reduce the size & compression time of the image with leasteffect on its quality .
  • 4. What is IMAGE COMPRESSION ? Application of data compression ondigital images Reduce redundancy in the image dataBenefits of IMAGE COMPRESSION . Store data efficiently Transmit data efficiently
  • 5. MEDICAL IMAGE COMPRESSION . Production of visual representations of bodyparts, tissues or organs Used in clinical diagnosis Encompasses X-ray methods , MRI & CT ScanDifferences From Normal IMAGE .Significant information in a small area Monochromatic background colour .
  • 6. What is JPEG Compression ? Stands for Joint Picture Experts Group Most popular LOSSY compression method Extensively used by digital cameras , mobiles & web usage Not suited for drawing , textual and iconic graphics Uses extensions – JPG or JPEG
  • 7. Basics of JPEG Compression  Human vision insensitive to Original high spatial frequencies image [ 150KB ]  High frequencies more coarsely compressed & Frequency filtered Domain image  Application of HPF  Image stored as frequency JPEG data image [ 14KB ]
  • 8. The JPEG Compression Algorithm Original image [ 150KB ] 8x8 RGB pixel To DCT Quantization Zigzag blocks YCbCr scan Huffman Encoding RLE JPEG Compressed Data [ 14 KB ] 100100010001000100100001111100010100
  • 9. 1/6 : 8x8 Block splitting
  • 10. 2/6 : Convert RGB to YCbCr
  • 11. 3/6 : Apply 2D Discrete Cosine Transformation [ DCT ] DCT Result
  • 12. 4/6 : Quantization DCT result Quantization Matrix Quantization result
  • 13. 5/6 : Zigzag Scan + RLE Zigzag scan
  • 14. 6/6 : Huffman Encoding Values G Real saved values  RLE result: . [0, -3] [0, 12] [0, 0 0 0,1 3]......EOB -1, 1 1 00, 01, 10, 11 -3, -2, 2, 3 2 000,001,010,011,100,101,110,111  After group number added: -7,-6,-5,-4,5,6,7 3 . [0,2,00b] [0,4,1100b] . 4 . [0,2,00b] . 5 . ...... EOB . . . . . .  First Huffman coding (i.e. for . . . [0,2,00b] ): . . . [0, 2, 00b] => [100b, . . . 00b] . . . . . -32767..32767 15
  • 15. The JPEG Decompression Algorithm 100100010001000100100001111100010100 JPEG Compressed Data [ 14 KB ] Huffman Zigzag RLE To Quantization IDCT Decoding 8x8 Multiplication Matrix YCbCr Image To Reconstruction RGB Decoded image [ 150KB ]
  • 16. Basic TERMS used : PSNR : Ratio between the maximum possible power of a signal and the power of its corrupting noise . MSE : The difference between an estimator and the true value of the quantity being estimated.
  • 17. Basic TERMS used : CR : The reduction in data-representation size produced by a data compression algorithm. BITRATE : Number of bits that are used for representing a pixel .
  • 18. Our Results of Normal Image using DCT Variation of Image Parameters with BITRATE 200 180 160 90 % 60 % 140 120 100 CR 80 MSE 60 PSNR 40 20 0 40 % 20 % 0 0.2 0.4 0.6 0.8 1 BITRATE PEPPERS IMAGE
  • 19. Our Results of Medical Image using DCT Variation of Image Parameters with BITRATE 50 45 40 35 90 % 60 % 30 25 CR 20 MSE 15 PSNR 10 5 0 0 0.2 0.4 0.6 0.8 1 40 % 20 % BITRATE CAT SCAN IMAGE
  • 20. Our Results of Medical Image using DCT Variation of Image Parameters with BITRATE 60 50 90 % 60 % 40 30 CR MSE 20 PSNR 10 0 0 0.2 0.4 0.6 0.8 1 40 % 20 % BITRATE X-RAY IMAGE
  • 21. Tasks left in our project Image Compression using DWT , JPEG2000 & SPIHT RLE Coding using Arithmetic codingtechnique Comparison & conclusion about thebest method
  • 22. Applications of Medical Image Compression Magnetic resonance imaging (MRI) Breast Thermography Tomography Ultrasound X-Rays Scientigraphy
  • 23. Any