DocumentCode
3543575
Title
An iterative least-square training method for classification-based motion adaptive temporal filtering
Author
Kim, Sung Deuk ; Lim, Kyoung Won
Author_Institution
Andong Nat. Univ., Andong, South Korea
fYear
2010
fDate
9-13 Jan. 2010
Firstpage
389
Lastpage
390
Abstract
This paper presents a motion-adaptive temporal filtering scheme based on trained least-square filtering. A novel iterative method is utilized in the training stage to find the optimal motion-adaptive temporal filter coefficient. The proposed approach shows optimal noise reduction performance in the LMS sense without introducing any blur.
Keywords
IIR filters; adaptive filters; image classification; image denoising; image motion analysis; iterative methods; least mean squares methods; optimisation; IIR filter; classification-based motion adaptive temporal filtering scheme; iterative least-square training method; least square optimization method; least-square filtering; optimal motion-adaptive temporal filter coefficient; optimal noise reduction performance; Adaptive filters; Detectors; Error correction; Filtering; Iterative methods; Least squares methods; Motion detection; Noise reduction; Optimization methods; Piecewise linear techniques;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics (ICCE), 2010 Digest of Technical Papers International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4244-4314-7
Electronic_ISBN
978-1-4244-4316-1
Type
conf
DOI
10.1109/ICCE.2010.5418818
Filename
5418818
Link To Document