%0 Journal Article
%T Pipelined Execution of Windowed Image Computations
%A Ramachandran Vaidyanathan
%A Phaneendra Vinukonda
%A Alyssa C. Lessing
%J International Journal of Networking and Computing
%D 2013
%I Hiroshima University
%X Many image processing operations manipulate an individual pixel using the values of other pixels in the neighborhood. Such operations are called windowed operations. The size of the windowed operation is a measure of the size of the given pixel's neighborhood. A windowed computation applies a windowed operation on all pixels of the image. An image processing application is typically a sequence of windowed computations. While windowed computations admit high parallelism, the cost of inputting and outputting the image often restricts the computation to a few computational units. In this paper we analytically study the running of a sequence of z windowed computations, each of size w, on a z-stage pipelined computational model. For an N¡ÁN image and n¡Án input/output bandwidth per stage, we show that the sequence of windowed computations can be run in at most N2/n2(1+¦Ä) steps, where ¦Ä=(n/N+6n3/(wN2)+zw/N+zn2N2). This produces a speed-up of z/(1+¦Ä) over a single stage; delta, the overhead is quite small. We also show that the memory requirement per stage is O(wN+n2). With values of N, n and w that reflect the current state-of-the-art, over 20 pipeline stages can be sustained with less than 5% overhead for a 10M-pixel image. Each of these stages would require less than 128 Kbytes of storage.
%K image processing
%K pipelining
%K windowed computation
%U http://www.ijnc.org/index.php/ijnc/article/view/54