Paper
30 April 1992 Unifying concepts in architecture-independent parallel image processing in Adapt
Jon A. Webb
Author Affiliations +
Proceedings Volume 1659, Image Processing and Interchange: Implementation and Systems; (1992) https://doi.org/10.1117/12.58410
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
Adapt is a data parallel little language for both local and global image processing on parallel computers. It is architecture independent: it hides the distribution of data, the number of processors and their topology, and even the existence of multiple processes from the programmer. The programs Adapt generates are efficient, even as compared with hand code, are easy to compile for MIMD architectures, and are easy to write. Adapt presents the programmer with three underlying concepts: the idea of the split and merge programming model, raster order per-pixel processing, and the scanline/transpose method. These three concepts make it possible to implement a wide variety of image processing algorithms, including histogram, uniform convolution, run-length encoding, image warping, connected components analysis, and two-dimensional fast Fourier transform. Performance of Adapt on Sun/Unix workstations, the Carnegie Mellon Warp machine, and the Carnegie Mellon - Intel Corporation iWarp computer will be presented. Adapt is being used in an implementation of the emerging ISO/ANSI standard Programmer's Imaging Kernel System. The implementation strategy of the library will be discussed.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jon A. Webb "Unifying concepts in architecture-independent parallel image processing in Adapt", Proc. SPIE 1659, Image Processing and Interchange: Implementation and Systems, (30 April 1992); https://doi.org/10.1117/12.58410
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KEYWORDS
Image processing

Raster graphics

Computing systems

Computer programming

Cameras

Digital filtering

Fourier transforms

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