The Blind Deconvolution Algorithm can be used effectively when no information about the distortion (blurring and noise) is known. The algorithm restores the image and the point-spread function (PSF) simultaneously. The accelerated, damped Richardson
We propose a maximum a posteriori blind Poissonian images deconvolution approach with framelet regularization for the image and total variation (TV) regularization for the point spread function. Compared with the TV based methods, our algorithm not
运动图像去模糊算法 We discuss a few new motion deblurring problems that are significant to kernel estimation and non-blind deconvolution. We found that strong edges do not always profit kernel estimation, but instead under certain circumstance degrade it. This
A blind deconvolution algorithm with modified Tikhonov regularization is introduced. To improve the spectral resolution, spectral structure information is incorporated into regularization by using the adaptive term to distinguish the spectral structu
The images recorded by a ground-based telescope are often degraded by atmospheric turbulence and the aberration of the optical system. Phase diversity-based blind deconvolution is an effective post-processing method that can be used to overcome the t
The blind image deconvolution techniques with sparsity prior in gradient domain are sensitive to noise, even a small amount of noise. To address this roblem, in this letter, we propose a novel blind deconvolution model that combines lowrank property,
Blind deconvolution of adaptive optics images plays an important role in the area of space object surveillance and astronomical imaging. This paper proposes a high resolution blind restoration method for adaptive optics images based on wavelength div
In this paper, we consider the use of blind deconvolution for optoacoustic (photoacoustic) imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the
