TY - GEN
T1 - Increasing computational redundancy of digital images via multiresolutional matching
AU - Khalvati, Farzad
AU - Tizhoosh, Hamid R.
AU - Hajian, Arsen R.
PY - 2009
Y1 - 2009
N2 - Computational redundancy of an image represents the amount of computations that can be skipped to improve performance. In order to calculate and exploit the computational redundancy of an image, a similarity measure is required to identify similar neighborhoods of pixels in the image. In this paper, we present two similarity measures: a position-invariant histogram-based measure and a rotation-invariant multiresolutional histogrambased measure. We demonstrate that by using the position-invariant and rotation-invariant similarity measures, on average, the computational redundancy of natural images increases by 34% and 28%, respectively, in comparison to the basic similarity measure. The increase in computational redundancy can lead to further performance improvement. For a case study, the average increase in actual speedup is 211% and 35% for position-invariant and rotation-invariant similarity measures, respectively.
AB - Computational redundancy of an image represents the amount of computations that can be skipped to improve performance. In order to calculate and exploit the computational redundancy of an image, a similarity measure is required to identify similar neighborhoods of pixels in the image. In this paper, we present two similarity measures: a position-invariant histogram-based measure and a rotation-invariant multiresolutional histogrambased measure. We demonstrate that by using the position-invariant and rotation-invariant similarity measures, on average, the computational redundancy of natural images increases by 34% and 28%, respectively, in comparison to the basic similarity measure. The increase in computational redundancy can lead to further performance improvement. For a case study, the average increase in actual speedup is 211% and 35% for position-invariant and rotation-invariant similarity measures, respectively.
KW - Computational Redundancy
KW - Histogram Matching
KW - Multiresolution Histogram Matching
UR - http://www.scopus.com/inward/record.url?scp=70350246252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350246252&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02611-9_15
DO - 10.1007/978-3-642-02611-9_15
M3 - Conference contribution
AN - SCOPUS:70350246252
SN - 3642026109
SN - 9783642026102
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 146
EP - 157
BT - Image Analysis and Recognition - 6th International Conference, ICIAR 2009, Proceedings
T2 - 6th International Conference on Image Analysis and Recognition, ICIAR 2009
Y2 - 6 July 2009 through 8 July 2009
ER -