A SVD Based Image Complexity Measure
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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A SVD Based Image Complexity Measure. / Gustafsson, David Karl John; Pedersen, Kim Steenstrup; Nielsen, Mads.
VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS. Bind 2 2009. s. 34-39.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - A SVD Based Image Complexity Measure
AU - Gustafsson, David Karl John
AU - Pedersen, Kim Steenstrup
AU - Nielsen, Mads
N1 - Conference code: 4
PY - 2009
Y1 - 2009
N2 - Images are composed of geometric structures and texture, and different image processing tools - such as denoising, segmentation and registration - are suitable for different types of image contents. Characterization of the image content in terms of geometric structure and texture is an important problem that one is often faced with. We propose a patch based complexity measure, based on how well the patch can be approximated using singular value decomposition. As such the image complexity is determined by the complexity of the patches. The concept is demonstrated on sequences from the newly collected DIKU Multi-Scale image database.
AB - Images are composed of geometric structures and texture, and different image processing tools - such as denoising, segmentation and registration - are suitable for different types of image contents. Characterization of the image content in terms of geometric structure and texture is an important problem that one is often faced with. We propose a patch based complexity measure, based on how well the patch can be approximated using singular value decomposition. As such the image complexity is determined by the complexity of the patches. The concept is demonstrated on sequences from the newly collected DIKU Multi-Scale image database.
M3 - Article in proceedings
SN - 978-989-8111-69-2
VL - 2
SP - 34
EP - 39
BT - VISAPP 2009
Y2 - 5 February 2009 through 8 February 2009
ER -
ID: 9225418