Reverse Image Filtering with Clean and Noisy Filters

Lizhong Wang, Pierre-Alain Fayolle, Alexander Belyaev

Research output: Contribution to journalArticlepeer-review

Abstract

Given an image filter y=f (x), where x and y are input and output images,
respectively, reverse image filtering consists of rendering an approximation to x from y using the filter f(·) itself as a black box, without knowing the internal structure of the filter. In this paper, we propose to use modified Landweber iterations for reverse image filtering, evaluate the performance of our approach, and present applications to image deblurring and super-resolution. An important advantage of our approach over the existing reverse image filtering methods is high robustness to noise.
Original languageEnglish
JournalSignal, Image and Video Processing
Publication statusAccepted/In press - 6 Apr 2022

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