Data in medical images is very large and therefore for storage and/or transmission of these images, compression is essential. A method is proposed which provides high compression ratios for radiographic images with no loss of diagnostic quality. In the approach an image is first compressed at a high compression ratio but with loss, and the error image is then compressed losslessly. The resulting compression is not only strictly lossless, but also expected to yield a high compression ratio, especially if the lossy compression technique is good. A neural network vector quantizer (NNVQ) is used as a lossy compressor, while for lossless compression Huffman coding is used. Quality of images is evaluated by comparing with standard compression techniques available.
Robina AsrafMuhammad AkbarNoman M. Jafri
Robina AsrafM. Ali AkbarNoman M. Jafri
Armando J. PinhoAntónio J. R. Neves