Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 6, Pages: 1-7
P. Kavitha1* and Anna Saro Vijendran2
1Department of Computer Science, S.N.R. SONS College, Coimbatore – 641006, Tamil Nadu, India; [email protected] 2Department of Computer Applications, S.N.R. SONS College, Coimbatore – 641006, Tamil Nadu, India; [email protected]
*Author for Correspondence
Department of Computer Science, S.N.R. SONS College, Coimbatore – 641006, Tamil Nadu, India; [email protected]
Objective: The main objective of this research is to preserve the edges and also remove the noise from high dynamic range videos during filtering process. This methodology attempts to preserve the original quality of the videos and achieves the better compression ration by compressing it with the concern of the edge preservation details. Methods: The system proposes a novel edge preserving LLSURE (Local Linear Model, Stein’s Unbiased Risk Estimate) surface estimator mechanism which is based on an adaptive local linear model and the principle of Stein’s Unbiased Risk Estimate (SURE). Generally, pixels in the edges and near to the edge are affected during noise filtering. Here the LLSURE filter is extended by using Edge-preserving surface estimator. The proposed estimator is used to leave some noise in the vicinity of edges and improve those edges during denoising process. Finally Weighted Residual Mean Squares (WRMS) is used for compute the quality of estimator. Findings: The performance evaluation was conducted to prove the efficiency of the proposed methodology by comparing it with the existing approach called OCP based video coding technique. The performance evaluation is conducted in terms of the parameters called the Peak Signal to Noise Ratio, Mean Square Error and Maximum error comparison. The experimental tests conducted were proves that the proposed methodology can lead to efficient preservation of the edge details during noise removal than the existing methodologies. Conclusion: The proposed procedure can remove the noise correctly in continuity or surrounding regions of the surface, and preserve discontinuities at the same time.
Keywords: Edge Preserving, LLSURE, Mean Integrated Error, Weighted Residual Mean Squares
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