Resolution enhancement via probabilistic deconvolution of multiple degraded images
Pattern Recognition Letters - Special issue: Pattern recognition in remote sensing (PRRS 2004)
Edge-Forming Methods for Image Zooming
Journal of Mathematical Imaging and Vision
Efficient recursive multichannel blind image restoration
EURASIP Journal on Applied Signal Processing
Blind image deblurring driven by nonlinear processing in the edge domain
EURASIP Journal on Applied Signal Processing
Blind and semi-blind deblurring of natural images
IEEE Transactions on Image Processing
Blurred image restoration: A fast method of finding the motion length and angle
Digital Signal Processing
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This work extends the Bussgang blind equalization algorithm to the multichannel case with application to image deconvolution problems. We address the restoration of images with poor spatial correlation as well as strongly correlated (natural) images. The spatial nonlinearity employed in the final estimation step of the Bussgang algorithm is developed according to the minimum mean square error criterion in the case of spatially uncorrelated images. For spatially correlated images, the nonlinearity design is rather conducted using a particular wavelet decomposition that, detecting lines, edges, and higher order structures, carries out a task analogous to those of the (preattentive) stage of the human visual system. Experimental results pertaining to restoration of motion blurred text images, out-of-focus spiky images, and blurred natural images are reported.