A NOISE ESTIMATION APPROACH BY ASSEMBLING FAST EDGE DETECTION AND BLOCK BASED METHODS
School of Information Engineering, Yulin University, 719000, Yulin, China
Noise estimation is one of the most important research topics in image processing. Aishy and Eric had proposed a variance estimation method used in Gaussian white-noise, in which, a measure was provided to determine the homogeneous blocks and an analyser was used in calculating the homogeneities. The approach should present two shortcomings corresponding to structures and textures. One is that the blocks with edge textures should be considered as intensity-homogeneous blocks that could have an effect on estimation accuracy. The other is that some special blocks with high variance but low homogeneity could result in over estimation. In order to avoid the two shortcomings, in this paper we have proposed an improved noise estimation approach by combining fast edge detection and block based methods. The blocks hold continuous points were firstly excluded rejected by using fast edge detection method. The experimental results indicated that our method can avoid over estimation effectively in special conditions and can obtain more accurate results than the Aishy and Eric’s method did.