Geometric Level Set Methods in Imaging, Vision, and Graphics

pp 103-119

Multiplicative Denoising and Deblurring: Theory and Algorithms

  • Leonid Rudin
  • , Pierre-Luis Lions
  • , Stanley Osher

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In [447, 449, 450], a constrained optimization type of numerical algorithm for restoring blurry, noisy images was developed and successfully tested. In this paper we present both theoretical and experimental justification for the method. Our main theoretical results involve constrained nonlinear partial differential equations. Our main experimental results involve blurry images which have been further corrupted with multiplicative noise. As in additive noise case of [447, 450] our numerical algorithm is simple to implement and is nonoscillatory (minimal ringing) and noninvasive (recovers sharp edges).