TY - GEN
T1 - Perfect window memoization
T2 - 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
AU - Khalvati, Farzad
AU - Tizhoosh, Hamid R.
PY - 2011
Y1 - 2011
N2 - This work presents Perfect Window Memoization; a high-level processing model that gives an estimation (upper-bound) of performance gain for an image processed in software or hardware, obtained by eliminating the computational redundancy of the image. We show mathematically, supported by experimental data, that the computational redundancy of an image is, in fact, inherited from two basic data redundancies of the image; coding and interpixel redundancy. This is a simple, yet a revealing concept to use in practice by which images can be categorized based on their potential performance gain in software and hardware by only their fundamental redundancies, with no need to implement a mechanism to actually exploit the computational redundancy in software or hardware. The proposed model can be used as a useful tool in analyzing images from the performance perspective in the early stages of designing an optimization technique.
AB - This work presents Perfect Window Memoization; a high-level processing model that gives an estimation (upper-bound) of performance gain for an image processed in software or hardware, obtained by eliminating the computational redundancy of the image. We show mathematically, supported by experimental data, that the computational redundancy of an image is, in fact, inherited from two basic data redundancies of the image; coding and interpixel redundancy. This is a simple, yet a revealing concept to use in practice by which images can be categorized based on their potential performance gain in software and hardware by only their fundamental redundancies, with no need to implement a mechanism to actually exploit the computational redundancy in software or hardware. The proposed model can be used as a useful tool in analyzing images from the performance perspective in the early stages of designing an optimization technique.
KW - Coding redundancy
KW - Interpixel redundancy
KW - Markov model
KW - Performance optimization
KW - Window memoization
UR - http://www.scopus.com/inward/record.url?scp=84864918756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864918756&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84864918756
SN - 9781601321916
T3 - Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
SP - 836
EP - 842
BT - Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Y2 - 18 July 2011 through 21 July 2011
ER -