Name
Abstract | ||
|---|---|---|
Vector quantizer takes care of special image features like edges also and hence belongs to the class of quantizers known as second generation coders This paper proposes a vector quantization using wavelet transform and enhanced SOM algorithm for medical image compression We propose the enhanced self-organizing algorithm to improve the defects of SOM algorithm, which, at first, reflects the error between the winner node and the input vector to the weight adaptation by using the frequency of the winner node Secondly, it adjusts the weight in proportion to the present weight change and the previous weight change as well To reduce the blocking effect and improve the resolution, we construct vectors by using wavelet transform and apply the enhanced SOM algorithm to them Our experimental results show that the proposed method energizes the compression ratio and decompression ratio. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30549-1_9 | Australian Conference on Artificial Intelligence |
Keywords | Field | DocType |
vector quantization,winner node,enhanced self-organizing algorithm,weight adaptation,previous weight change,enhanced som algorithm,som algorithm,medical image vector quantizer,vector quantizer,input vector,present weight change,wavelet transform | Computer science,Feature (computer vision),Algorithm,Compression ratio,Vector quantization,Data compression,Quantization (signal processing),Stationary wavelet transform,Image compression,Wavelet transform | Conference |
Volume | ISSN | ISBN |
3339 | 0302-9743 | 3-540-24059-4 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| kwangbaek kim | 1 | 110 | 43.94 |
| Gwang-Ha Kim | 2 | 5 | 1.52 |
| Sung-Kwan Je | 3 | 6 | 4.30 |