Deblurring Shaken and Partially Saturated Images

Oliver Whyte 1, 2 Josef Sivic 1, 2 Andrew Zisserman 1, 2, 3
2 WILLOW - Models of visual object recognition and scene understanding
DI-ENS - Département d'informatique de l'École normale supérieure, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : We address the problem of deblurring images degraded by camera shake blur and saturated (over-exposed) pixels. Saturated pixels violate the common assumption that the image-formation process is linear, and often cause ringing in deblurred outputs. We provide an analysis of ringing in general, and show that in order to prevent ringing, it is insufficient to simply discard saturated pixels. We show that even when saturated pixels are removed, ringing is caused by attempting to estimate the values of latent pixels that are brighter than the sensor's maximum output. Estimating these latent pixels is likely to cause large errors, and these errors propagate across the rest of the image in the form of ringing. We propose a new deblurring algorithm that locates these error-prone bright pixels in the latent sharp image, and by decoupling them from the remainder of the latent image, greatly reduces ringing. In addition, we propose an approximate forward model for saturated images, which allows us to estimate these error-prone pixels separately without causing artefacts. Results are shown for non-blind deblurring of real photographs containing saturated regions, demonstrating improved deblurred image quality compared to previous work.
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Article dans une revue
International Journal of Computer Vision, Springer Verlag, 2014, 〈10.1007/s11263-014-0727-3〉
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Oliver Whyte, Josef Sivic, Andrew Zisserman. Deblurring Shaken and Partially Saturated Images. International Journal of Computer Vision, Springer Verlag, 2014, 〈10.1007/s11263-014-0727-3〉. 〈hal-01053888〉

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