Yanhao Li, Marina Gardella, Quentin Bammey, Tina Nikoukhah, Rafael Grompone von Gioi, Miguel Colom, Jean-Michel Morel
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A Signal-dependent Video Noise Estimator Via Inter-frame Signal Suppression
We propose a block-based signal-dependent noise estimation method on videos, that leverages inter-frame redundancy to separate noise from signal. Block matching is applied to find block pairs between two consecutive frames with similar signal. Then the Ponomarenko et al. method is extended to video by sorting pairs by their low-frequency energy and estimating noise in the high frequencies. Experiments on a real dataset of drone videos show its performance for different parameter settings and different noise levels. Two extensions of the proposed method using subpixel matching and for multiscale noise estimation are respectively analyzed.
期刊介绍：
IPOL publishes relevant image processing and image analysis algorithms emphasizing the role of mathematics as a source for algorithm design. The publication is as precise and comprehensive as possible. To this aim, the publication of each algorithm is fourfold and includes: a manuscript containing the detailed description of the published algorithm, of its bibliography, along with commented examples and a failure case analysis; a software implementation of the algorithm in C, C++ or Matlab; an online demo, where the algorithm can be tested on data sets uploaded by the users; an archive containing extensive online experiments. The restricted goal of IPOL is to make accessible the algorithms in their uttermost explicit form to the scientific community. The publication of an algorithm by IPOL is different from, and complementary to a classic journal publication.
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