Comparison of discrete cosine transform and vector quantization of medical imagery

Barry G. Haskell, Hsueh Ming Hang

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations


This paper addresses the problem of data compression of medical imagery such as X-rays, Computer Tomography, Magnetic Resonance, Nuclear Medicine and Ultrasound. The Discrete Cosine Transform (DCT) has been extensively studied for image data compression, and good compression has been obtained without unduly sacrificing image quality. Vector Quantization has only recently been applied to image data compression, but shows promise of outperforming more traditional transform coding methods, especially at high compression. Vector Quantization is quite well suited for those applications where the images to be processed are very much alike, or can be grouped into a small number of classifications. These and similar studies continue to suffer from the lack of a uniformly agreed upon measure of image quality. This is also exacerbated by the large variety of electronic displays and viewing conditions.

Original languageEnglish
Pages (from-to)399-408
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 12 Jun 1986
EventApplication of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems (PACS IV) for Medical Applications 1986 - Newport Beach, United States
Duration: 2 Feb 19867 Feb 1986


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