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In this paper, we propose anew performance technique for exact computation on window memoization algorithminstead of tolerant window memoization. Window memoization is a technique inthe field of local image processing that benefit memoization method and dataredundancy on images to improve speedups of computation performance by eliminating computational redundancy.In tolerant method a number of LSBs bits of neighborhood pixels in thewindows are eliminated to lead to increase the probability of having similarwindows in an image and it cause to gain the speedups computations performanceby skipping the computation of similar windows, but only using MSBs bits and eliminatingLSBs bits of neighborhood pixels in the window cause accuracy loss in theresults.In the other hand some imaging devices make more bits per pixel, forexample MRI, PET, CT in medical imaging devices and Ultra High Definition TV incommercial device, that make 10 to 16 bits per pixels, for this reasons it’snecessary to have a method to support high depth of pixel without eliminatingLSBs bits and have accurate results and also acceptable speedups.We have developed this optimized method onsoftware and applied edge detector to natural and medical images of 512x512pixels and the typical speedups is 1.29x and 1.42x in comparison toconventional method and also without accuracy loss in the results.

An optimized Window Memoization Architecture for High Performance and Accurate Image Processing