Medical image vector quantizer using wavelet transform and enhanced SOM algorithm

  • Authors:

  • Kwang-Baek Kim;Gwang-Ha Kim;Sung-Kwan Je

  • Affiliations:

  • Dept of Computer Engineering, Silla University, Busan, Korea;Dept of Internal Medicine, Pusan National University College of Medicine, Busan, Korea;Dept of Computer Science, Pusan National University, Busan, Korea

  • Venue:
  • AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

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.