Wavelet-content-adaptive BP neural network-based deinterlacing algorithm
Author:
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
http://link.springer.com/article/10.1007/s00500-017-2968-x/fulltext.html
Reference23 articles.
1. Aggarwal U, Trocan M, Coudoux F-X (2017) An HVS-inspired video deinterlacer based on visual saliency. Vietnam J Comput Sci 4(1):6169
2. Bellars EB, De Haan G (2000) Deinterlacing: a key technology for scan rate conversion. Elsevier, Amsterdam
3. Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8:679–698
4. Chen P-Y, Lai Y-H (2007) A low-complexity interpolation method for deinterlacing. IEICE Trans Inf Syst E90–D(2):606608
5. Chen T, Wu HR, Yu ZH (2000) Efficient deinterlacing algorithm using edge-based line average interpolation. Opt Eng 39(8):21012105
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