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 Tai
Speaker: Hsien-Chu Wu
Date: 02/21/2002
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Outline
• Introduction
• Proposed strategy
• Simulation results
• Conclusions
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IntroductionGoal: Develop a strategy to raise the compression ration by exploiting spectra similarity while preserving good decoded quality.
Observation:
4
Proposed Strategy
A. Spectrum Reorganization
Need a buffer to store all individual 88 DCT transformed data sequentially
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5
Proposed Strategy
B. Band Similarity for Further Bit-Rate Reduction
1. Quantization
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Proposed Strategy
2. Discarding the insignificant bands
it discard and band
ant insignific an as assign ), threshold( If
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7
Proposed Strategy
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9
Simulation Results
Fig. 1 Decoded angiogram by the proposed method
Fig. 2 Decoded angiogram by
JPEG
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(a) (b)
(c)Fig. 3. Test of angiogram image; (a) Original image;(b)Bit rate =0.22 bpp, PSNR=44.98dB;(c)Difference image
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(a) (b)
Fig. 4. Test of angiogram image; (a) Original image;(b)Bit rate =0.55 bpp, PSNR=38.11dB;(c)Difference image
(c)
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Simulation Results
Table 1 Performance comparison of JPEG and the proposed method
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Simulation Results
Fig. 5. Chart of performance comparison
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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.
