Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Multidimensional Systems and Signal Processing
Selection of Optimal Stopping Time for Nonlinear Diffusion Filtering
International Journal of Computer Vision
Total variation minimizing blind deconvolution with shock filter reference
Image and Vision Computing
A regularization approach to joint blur identification and image restoration
IEEE Transactions on Image Processing
Total variation blind deconvolution
IEEE Transactions on Image Processing
Fast, robust total variation-based reconstruction of noisy, blurred images
IEEE Transactions on Image Processing
Bayesian and regularization methods for hyperparameter estimation in image restoration
IEEE Transactions on Image Processing
The digital TV filter and nonlinear denoising
IEEE Transactions on Image Processing
Estimation of optimal PDE-based denoising in the SNR sense
IEEE Transactions on Image Processing
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Blind restoration of aerial multipspectral images, through a sequential deconvolution scheme is addressed in this paper. The proposed scheme is composed of three successive optimized processes : image denoising followed by Point Spread Function (PSF) estimation and finally image restoration. First, an iterative denoising filter is applied and stopped at the iteration when an optimal estimation of the blurry image is obtained. Secondly, slighty TV (Total Variation) regularized PSF estimation is carried out on an almost noise free version of the blurry image. In order to keep unknown original image fixed during PSF estimation, shocked filtering of filtered image is efficiently considered. Thirdly, assuming the previously estimated PSF fixed, a TV-regularized deconvolution is performed on filtered image to give better estimation of original image. Regularization parameters are automatically tuned using regularization-scale relationship. Results obtained on aerial CASI and AISA Eagle multispectral images prove efficacy of the proposed scheme.