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
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Minimal operator set for passive depth from defocus
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Learning How to Inpaint from Global Image Statistics
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
ACM SIGGRAPH 2005 Papers
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
Fast separation of direct and global components of a scene using high frequency illumination
ACM SIGGRAPH 2006 Papers
Image Completion Using Global Optimization
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)
Veiling glare in high dynamic range imaging
ACM SIGGRAPH 2007 papers
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
Glare aware photography: 4D ray sampling for reducing glare effects of camera lenses
ACM SIGGRAPH 2008 papers
ACM SIGGRAPH 2008 papers
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Priors for Large Photo Collections and What They Reveal about Cameras
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Automated removal of partial occlusion blur
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Contrast restoration of weather degraded images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dirty glass: rendering contamination on transparent surfaces
EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
Inpainting in multi-image stereo
Proceedings of the 32nd DAGM conference on Pattern recognition
Towards Unrestrained Depth Inference with Coherent Occlusion Filling
International Journal of Computer Vision
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Dirt on camera lenses, and occlusions from thin objects such as fences, are two important types of artifacts in digital imaging systems. These artifacts are not only an annoyance for photographers, but also a hindrance to computer vision and digital forensics. In this paper, we show that both effects can be described by a single image formation model, wherein an intermediate layer (of dust, dirt or thin occluders) both attenuates the incoming light and scatters stray light towards the camera. Because of camera defocus, these artifacts are low-frequency and either additive or multiplicative, which gives us the power to recover the original scene radiance pointwise. We develop a number of physics-based methods to remove these effects from digital photographs and videos. For dirty camera lenses, we propose two methods to estimate the attenuation and the scattering of the lens dirt and remove the artifacts -- either by taking several pictures of a structured calibration pattern beforehand, or by leveraging natural image statistics for post-processing existing images. For artifacts from thin occluders, we propose a simple yet effective iterative method that recovers the original scene from multiple apertures. The method requires two images if the depths of the scene and the occluder layer are known, or three images if the depths are unknown. The effectiveness of our proposed methods are demonstrated by both simulated and real experimental results.