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Medical Image Compression by Discrete Cosine Transform

Jun 27, 2015



  • 1. Medical Image Compression by Discrete Cosine Transform Spectral Similarity Strategy Source : IEEE Transactions on Information Technology in Biomedicine, Vol. 5, No. 3, Sept. 2001 Authors : Yung-Gi Wu and Shen-Chuan TaiSpeaker : Hsien-Chu Wu Date : 02/21/2002

2. Outline

  • Introduction
  • Proposed strategy
  • Simulation results
  • Conclusions

3. Introduction

  • Goal : Develop a strategy to raise the compression ration byexploiting spectra similarity while preserving good decoded quality.
  • Observation:

4. Proposed Strategy

  • A. Spectrum Reorganization
  • Need a buffer to store all individual 8 8 DCT transformeddata sequentially

5. Proposed Strategy

  • B. Band Similarity for Further Bit-Rate Reduction
  • 1. Quantization

6. Proposed Strategy

  • 2. Discarding the insignificant bands

7. Proposed Strategy

  • 3. Seeking a best similarity matching band for each significant band

8. 9. Simulation Results Fig. 1 Decoded angiogram by the proposed methodFig. 2 Decoded angiogram by JPEG 10. (a) (b) (c) Fig. 3. Test of angiogram image; (a) Original image;(b)Bit rate =0.22 bpp, PSNR=44.98dB;(c)Difference image 11. (a) (b) Fig. 4. Test of angiogram image; (a) Original image;(b)Bit rate =0.55 bpp, PSNR=38.11dB;(c)Difference image(c) 12. Simulation Results Table 1Performance comparison of JPEG and the proposed method 13. Simulation Results Fig. 5. Chart of performance comparison 14. Conclusions

  • Three major procedures, including band gathering, significance selection and band similarity matching having been presented to reduce the bit rate .
  • The proposed method is equal-sized sub-band decomposition and can achieved the perfect reconstruction without quantization.
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