DocumentCode :
3409595
Title :
Adaptable K-nearest neighbor for image interpolation
Author :
Ni, Karl S. ; Nguyen, Truong Q.
Author_Institution :
Dept of ECE, UCSD, La Jolla, CA
fYear :
2008
fDate :
March 31 2008-April 4 2008
Firstpage :
1297
Lastpage :
1300
Abstract :
A variant of the k-nearest neighbor algorithm is proposed for image interpolation. Instead of using a static volume or static k, the proposed algorithm determines a dynamic k that is small for inputs whose neighbors are very similar and large for inputs whose neighbors are dissimilar. Then, based on the neighbors that the adaptable k provides and their corresponding similarity measures, a weighted MMSE solution defines filters specific to intrinsic content of a low-resolution input image patch without yielding to the limitations of a non-uniformly distributed training set. Finally, global optimization through a single pass Markovian-like network further imposes on filter weights. The approach is justified by a sufficient quantity of relevant training pairs per test input and compared to current state of the art nearest neighbor interpolation techniques.
Keywords :
filtering theory; image processing; interpolation; least mean squares methods; optimisation; adaptable k-nearest neighbor algorithm; global optimization; image interpolation; low-resolution input image patch; optimal filters; single pass Markovian-like network; weighted MMSE solution; Algorithm design and analysis; Cities and towns; Estimation error; Heuristic algorithms; Image reconstruction; Interpolation; Nearest neighbor searches; Spline; Testing; Weight measurement; interpolation; nearest neighbor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
ISSN :
1520-6149
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2008.4517855
Filename :
4517855
Link To Document :
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