Low-level vision on Warp and the Apply programming model

Len Hamey, Jon Webb, I-Chen Wu

Research output: Chapter in Book/Report/Conference proceedingChapter


In computer vision, the first, and often most time-consuming, step in image processing is image-to-image operations. In this step, an input image is mapped into an output image through some local operation that applies to a window around each pixel of the input image. Algorithms that fall into this class include: edge detection, smoothing, convolutions in general, contrast enhancement, color transformations, and thresholding. Collectively, we call these operations low-level vision. Low-level vision is often time-consuming simply because images are quite large—a typical size is 512 × 512 pixels, so the operation must be applied 262,144 times.
Original languageEnglish
Title of host publicationParallel Computation and Computers for Artificial Intelligence
EditorsJanusz S. Kowalik
Place of PublicationNorwell, Massachusetts
PublisherKluwer Academic Publishers
Number of pages15
ISBN (Electronic)9781461319894
ISBN (Print)9781461291886, 9780898382273
Publication statusPublished - 1988
Externally publishedYes

Publication series

NameThe Springer International Series in Engineering and Computer Science


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