A novel algorithm for blind image deconvolution using the zero-lag slice (ZLS) of higher-order statistics only is presented. This method first estimates the point-spread function (PSF) using the ZLS of its third-order moment (TOM) and then uses it with one of the known classical image deconvolution methods. The proposed method has simple computations for PSF estimation because it solves a nonlinear problem by using an iterative method with fast convergence. In each iteration, one need only calculate the ZLS of the TOM and estimate the PSF using simple two-dimensional operations. Furthermore, the method presented achieves good results, since the ZLS estimate obtained from the degraded image exhibits high reliability. The good performance of the proposed algorithm is demonstrated by applying it to synthetic and real data sets.
[1]
Chong-Yung Chi,et al.
Two-dimensional frequency-domain blind system identification using higher order statistics with application to texture synthesis
,
2001,
IEEE Trans. Signal Process..
[2]
Blind deconvolution of spotted image based on slice selection of third-order moment
,
2003
.
[3]
Deepa Kundur,et al.
Blind Image Deconvolution
,
2001
.
[4]
Yehoshua Y. Zeevi,et al.
Quasi Maximum Likelihood Blind Deconvolution of Images Using Optimal Sparse Representations
,
2003
.
[5]
Wenkai Lu,et al.
Blind channel estimation using zero-lag slice of third-order moment
,
2005,
IEEE Signal Process. Lett..