Image Motion Estimation From Motion Smear-A New Computational Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-Based Motion Deblurring
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multilevel Banded Graph Cuts Method for Fast Image Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Removing camera shake from a single photograph
ACM SIGGRAPH 2006 Papers
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
High-quality motion deblurring from a single image
ACM SIGGRAPH 2008 papers
Progressive inter-scale and intra-scale non-blind image deconvolution
ACM SIGGRAPH 2008 papers
ACM SIGGRAPH Asia 2009 papers
Image deblurring using inertial measurement sensors
ACM SIGGRAPH 2010 papers
Robust web image/video super-resolution
IEEE Transactions on Image Processing
Two-phase kernel estimation for robust motion deblurring
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Image restoration in digital photography
IEEE Transactions on Consumer Electronics
CFA-based motion blur removal using long/short exposure pairs
IEEE Transactions on Consumer Electronics
Total variation blind deconvolution
IEEE Transactions on Image Processing
Blind image restoration by anisotropic regularization
IEEE Transactions on Image Processing
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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Image deblurring techniques play important roles in many image processing applications. As the blur varies spatially across the image plane, it calls for robust and effective methods to deal with the spatially-variant blur problem. In this paper, a Saliency-based Deblurring (SD) approach is proposed based on the saliency detection for salient-region segmentation and a corresponding compensate method for image deblurring. We also propose a PDE-based deblurring method which introduces an anisotropic Partial Differential Equation (PDE) model for latent image prediction and employs an adaptive optimization model in the kernel estimation and deconvolution steps. Experimental results demonstrate the effectiveness of the proposed algorithm.