Abstract
Similar images are images with common features, similar pixel distributions, and similar edge distributions. Fields such as medical imaging often need to store large collections of similar images. In a set of similar images the images similarities represent patterns that consistently appear across all images; this results in 'set redundancy'. Recently, the research of wavelet transformation is developed quickly and compression using wavelet is a good choice instead of DCT transform. In this paper, we present the Centroid method, which extracts the similarity coefficients obtained from wavelet transform, to reduce set redundancy and achieve higher compression ratio for sets of similar images. Experimental results with a set of CT images demonstrate that the Centroid method using wavelet can deliver significantly improved image compression. Compared with entropy coding and wavelet compression respectively, the proposed method is improved about 56% and 26%.
| Original language | English |
|---|---|
| Pages (from-to) | 133-140 |
| Number of pages | 8 |
| Journal | Chinese Journal of Medical and Biological Engineering |
| Volume | 20 |
| Issue number | 3 |
| State | Published - 2000 |
Keywords
- Centroid method
- Image compression
- Set redundancy
- Wavelet transform
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