Paper
1 July 1990 Comparative performance of pyramid data structures for progressive transmission of medical imagery
Limin Wang, Morris Goldberg
Author Affiliations +
Abstract
Progressive image transmission is receiving attention for application in interactive image communication over low-bandwidth channels. In progressive image transmission, a low-resolution image is first transmitted. Upon the user's request, the low-resolution image can be then refined progressively with further transmission until the original image is losslessly reproduced. One important class of encoding for progressive image transmission is based upon pyramid data structures where the intermediate levels correspond to reduced-resolution approximations. Progressive image transmission is achieved by sending the data stored in the pyramid starting from the top level. In this paper, we present a comparison of various pyramid data structures for progressive transmission of medical imagery. These pyramid data structures include the mean, reduced-sum, difference, reduced-difference, S-transform and Gaussian-Laplacian pyramids. The simulations are carried out on a set of digitized radiographic images. The simulation results demonstrate that the reduced-difference pyramid achieves the best performance in terms of three criteria: the equivalent entropy, rate distortion performance and total lossless transmission hit rate. Furthermore, the quality of the intermediate level images is seen to be improved by using an appropriate interpolation function.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Limin Wang and Morris Goldberg "Comparative performance of pyramid data structures for progressive transmission of medical imagery", Proc. SPIE 1232, Medical Imaging IV: Image Capture and Display, (1 July 1990); https://doi.org/10.1117/12.18878
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Cited by 10 scholarly publications.
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KEYWORDS
Image transmission

Medical imaging

Distortion

Digital imaging

Chest

Image resolution

Image restoration

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