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Deblurring Shaken and Partially Saturated Images


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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This work was partly supported by the MSR-INRIA laboratory, the EIT ICT labs and ERC grant VisRec no. 228180.

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Correspondence to Oliver Whyte.

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Communicated by Dr. Srinivas Narasimhan, Dr. Frédo Durand and Dr. Wolfgang Heidrich.

Parts of this work were previously published in the IEEE Workshop on Color and Photometry in Computer Vision, with ICCV 2011 Whyte et al. (2011).

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Whyte, O., Sivic, J. & Zisserman, A. Deblurring Shaken and Partially Saturated Images. Int J Comput Vis 110, 185–201 (2014).

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  • Non-blind deblurring
  • Saturation
  • Ringing
  • Outliers