Assorted Pixels: Multi-sampled Imaging with Structural Models
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Removing camera shake from a single photograph
ACM SIGGRAPH 2006 Papers
Coded exposure photography: motion deblurring using fluttered shutter
ACM SIGGRAPH 2006 Papers
Image deblurring with blurred/noisy image pairs
ACM SIGGRAPH 2007 papers
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2008 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
Invertible motion blur in video
ACM SIGGRAPH 2009 papers
ACM SIGGRAPH Asia 2009 papers
Image deblurring using inertial measurement sensors
ACM SIGGRAPH 2010 papers
Two-phase kernel estimation for robust motion deblurring
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Motion deblurring using hybrid imaging
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Linear demosaicing inspired by the human visual system
IEEE Transactions on Image Processing
Image Deconvolution With Multi-Stage Convex Relaxation and Its Perceptual Evaluation
IEEE Transactions on Image Processing
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Image deblurring has been a very challenging problem in recent decades. In this article, we propose a high-quality image deblurring method with a novel image prior based on a new imaging system. The imaging system has a newly designed sensor pattern achieved by adding panchromatic (pan) pixels to the conventional Bayer pattern. Since these pan pixels are sensitive to all wavelengths of visible light, they collect a significantly higher proportion of the light striking the sensor. A new demosaicing algorithm is also proposed to restore full-resolution images from pixels on the sensor. The shutter speed of pan pixels is controllable to users. Therefore, we can produce multiple images with different exposures. When long exposure is needed under dim light, we read pan pixels twice in one shot: one with short exposure and the other with long exposure. The long-exposure image is often blurred, while the short-exposure image can be sharp and noisy. The short-exposure image plays an important role in deblurring, since it is sharp and there is no alignment problem for the one-shot image pair. For the algorithmic aspect, our method runs in a two-step maximum-a-posteriori (MAP) fashion under a joint minimization of the blur kernel and the deblurred image. The algorithm exploits a combined image prior with a statistical part and a spatial part, which is powerful in ringing controls. Extensive experiments under various conditions and settings are conducted to demonstrate the performance of our method.