Selective image‐sharpness enhancement by coupled nonlinear reaction‐diffusion time‐evolution equations and its application to suppression of breathing distortions in moving pictures

Abstract

SUMMARYThe authors describe a technique for selectively sharpening only edges that were blurred due to various causes without making interference factors such as random noise more conspicuous. The selective sharpening technique described in this paper is implemented as an iterative updating nonlinear algorithm obtained by discretizing a type of nonlinear reaction-diffusion time-evolution equations. The update terms of this algorithm consist of a quadratic nonlinear smoothing term, reaction term, and overshooting term. By performing quantitative evaluation experiments, the authors showed that the proposed technique has significantly better selective sharpness enhancement capabilities than existing sharpness enhancement techniques such as the peaking method. In addition, the authors introduced a processing parameter adaptive control method in the proposed technique and applied it to the suppression of breathing distortions in video sequences. Breathing distortions, which are video sequence distortions that often appear in old films, are time-varying blurring distortions that occur due to temporal variations of the focus.

Model-based PDE method and model-free PDE method for motion de-blurring

“…On the other hand, the model-free PDE methods often use their transient solutions as a sharpened image. The typical methods of this category are the forward-and-backward diffusion method proposed by Gilboa, Sochen and Zeevi 6 , and our coupled nonlinear diffusion method 7,8 . They have been derived as the variations of the nonlinear diffusion process.…”