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» Maximum-Likelihood Image Matching
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TIP
1998
113views more  TIP 1998»
15 years 3 months ago
Best neighborhood matching: an information loss restoration technique for block-based image coding systems
—Imperfect transmission of block-coded images often results in lost blocks. A novel error concealment method called best neighborhood matching (BNM) is presented by using a speci...
Zhou Wang, Yinglin Yu, David Zhang
ICCV
2011
IEEE
14 years 3 months ago
Coherency Sensitive Hashing
Coherency Sensitive Hashing (CSH) extends Locality Sensitivity Hashing (LSH) and PatchMatch to quickly find matching patches between two images. LSH relies on hashing, which maps...
Simon Korman, Shai Avidan
ICIP
2005
IEEE
15 years 9 months ago
Image matching based on a local invariant descriptor
— Image matching is a fundamental task of many computer vision problems. In this paper we present a novel approach to match two images in presenting significant geometric deform...
Lei Qin, Wen Gao
WWW
2009
ACM
16 years 4 months ago
Detecting image spam using local invariant features and pyramid match kernel
Image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. In this paper, we extract local invariant features ...
Haiqiang Zuo, Weiming Hu, Ou Wu, Yunfei Chen, Guan...
CVPR
2007
IEEE
15 years 9 months ago
High Distortion and Non-Structural Image Matching via Feature Co-occurrence
We propose a novel approach for determining if a pair of images match each other under the effect of a highdistortion transformation or non-structural relation. The co-occurrence ...
Xi Chen, Tat-Jen Cham