Compression of medical images through adaptive block-size DCT coding
Man Nang Chong, E.L. Ang, C. S. Tan, Chueh Loo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
Compression of medical images to reduce their storage and transmission bandwidth requirements is of great interest in the implementation of systems such as the picture archiving and communication system (PACS). Direct application of discrete cosine transform (DCT) coding to medical images such as CT or MRI images is not effective as the characteristics of such medical images are not exploited. Firstly, the noisy background in medical images exhibits largely uncorrelated data which is difficult to compress using transform coding. Secondly, the overhead in representing the background information using fixed block-size transform coding is inefficient. A novel adaptive coding algorithm is proposed to yield high compression rate for medical images. The proposed algorithm is a two-stage process: the first stage (pre-processing stage) attempts to remove the background noise and identifies the border of the medical data by using a visual mask; the second stage (encoding stage) uses an adaptive block-size DCT coding algorithm to compress the image data. The proposed coding algorithm is evaluated and compared with the JPEG baseline algorithm where results on the compression ratio and peak signal-to-noise ratio (PSNR) are presented. The results show that the proposed coding algorithm achieves a higher compression rate than the JPEG baseline algorithm. In addition, the PSNR values of the new coder is marginally higher than the results obtained with the JPEG coder.