Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Fundamentals of digital image processing
Fundamentals of digital image processing
Arithmetic coding for data compression
Communications of the ACM
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
IEEE Transactions on Computers
An adaptive 3-D discrete cosine transform coder for medical image compression
IEEE Transactions on Information Technology in Biomedicine
Medical image compression by discrete cosine transform spectral similarity strategy
IEEE Transactions on Information Technology in Biomedicine
Medical image compression by sampling DCT coefficients
IEEE Transactions on Information Technology in Biomedicine
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
International Journal of Telemedicine and Applications
| Hi-index | 0.00 |
Telemedicine, among other things, involves storage and transmission of medical images, popularly known as teleradiology. Due to constraints on bandwidth and storage capacity, a medical image may be needed to be compressed before transmission/storage. Among various compression techniques, transform-based techniques that convert an image in spatial domain into the data in spectral domain are very effective. Discrete cosine transform (DCT) is possibly the most popular transform used in compression of images in standards like Joint Photographic Experts Group (JPEG). In DCT-based compression the image is split into smaller blocks for computational simplicity. The blocks are classified on the basis of information content to maximize compression ratio without sacrificing diagnostic information. The present paper presents a technique along with computational algorithm for classification of blocks on the basis of an adaptive threshold value of variance. The adaptive approach makes the classification technique applicable across the board to all medical images. Its efficacy is demonstrated by applying it to CT, X-ray and ultrasound images and by comparing the results against the JPEG in terms of various objective quality indices.