We address the problem of inpainting noisy photographs. We present a recursive image recovery scheme based on the unscented Kalman filter (UKF) to simultaneously inpaint identified damaged portions in an image and suppress film-grain noise. Inpainting of the missing observations is guided by a mask-dependent reconstruction of the image edges. Prediction within the UKF is based on a discontinuity-adaptive Markov random field prior that attempts to preserve edges while achieving noise reduction in uniform regions. We demonstrate the capability of the proposed method with many examples.
© 2010 Optical Society of America
Original Manuscript: August 18, 2009
Revised Manuscript: February 1, 2010
Manuscript Accepted: February 1, 2010
Published: April 16, 2010
G. R. K. S. Subrahmanyam, A. N. Rajagopalan, and R. Aravind, "Recursive framework for joint inpainting and de-noising of photographic films," J. Opt. Soc. Am. A 27, 1091-1099 (2010)