caa a22 4500 44529535X CHVBK 20180317142540.0 cr unu---uuuuu 170323e20100901xx s 000 0 eng 10.1007/s11554-009-0128-y doi (NATIONALLICENCE)springer-10.1007/s11554-009-0128-y Window memoization: an efficient hardware architecture for high-performance image processing [Elektronische Daten] [Farzad Khalvati, Mark Aagaard] This work presents a new performance improvement technique, window memoization, for hardware implementations of local image processing algorithms. Window memoization combines the memoization techniques proposed in software and hardware with data redundancy in image processing to improve the efficiency of local image processing algorithms implemented in hardware. It minimizes the number of redundant computations performed on an image by identifying similar neighborhoods of pixels in the image and skipping the redundant computations. We have developed an optimized architecture in hardware that embodies the window memoization technique. Our hardware design for window memoization achieves high speedups with an overhead in hardware area that is significantly less than that of the conventional performance improvement techniques. As case studies in hardware, we have applied window memoization to the Kirsch edge detector and median filter. The typical speedup factor in hardware is 1.58 with 40% less hardware in comparison to conventional optimization techniques. Springer-Verlag, 2009 Computational redundancy nationallicence Memoization nationallicence Reuse nationallicence High-performance and efficient real-time image processing nationallicence Hardware architecture nationallicence Khalvati Farzad Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada aut Aagaard Mark Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada aut Journal of Real-Time Image Processing Springer-Verlag 5/3(2010-09-01), 195-212 1861-8200 5:3<195 2010 5 11554 https://doi.org/10.1007/s11554-009-0128-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11554-009-0128-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Khalvati Farzad Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada aut NATIONALLICENCE 700 1- Aagaard Mark Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada aut NATIONALLICENCE 773 0- Journal of Real-Time Image Processing Springer-Verlag 5/3(2010-09-01), 195-212 1861-8200 5:3<195 2010 5 11554 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer