Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Vector Quantization for Medical Image Compression Based on DCT and Fuzzy C-Means

  • Supot, Sookpotharom (Dept. of Electrical Engineering, Bangkok University) ;
  • Nopparat, Rantsaena (Dept. of Electronics, Faculty of Engineering, King Mongkut Institute of Technology Ladkrabang(KMITL)) ;
  • Surapan, Airphaiboon (Dept. of Electronics, Faculty of Engineering, King Mongkut Institute of Technology Ladkrabang(KMITL)) ;
  • Manas, Sangworasil (Dept. of Electronics, Faculty of Engineering, King Mongkut Institute of Technology Ladkrabang(KMITL))
  • Published : 2002.07.01
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Abstract

Compression of magnetic resonance images (MRI) has proved to be more difficult than other medical imaging modalities. In an average sized hospital, many tora bytes of digital imaging data (MRI) are generated every year, almost all of which has to be kept. The medical image compression is currently being performed by using different algorithms. In this paper, Fuzzy C-Means (FCM) algorithm is used for the Vector Quantization (VQ). First, a digital image is divided into subblocks of fixed size, which consists of 4${\times}$4 blocks of pixels. By performing 2-D Discrete Cosine Transform (DCT), we select six DCT coefficients to form the feature vector. And using FCM algorithm in constructing the VQ codebook. By doing so, the algorithm can make good time quality, and reduce the processing time while constructing the VQ codebook.

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