Enhancing image denoising by controlling noise incursion in learned dictionaries
Sahoo, Sujit Kumar
Anamitra Makur (EEE)
Date of Issue2015
School of Electrical and Electronic Engineering
Existing image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and provides a simple remedy for a desired signal to noise ratio. The remedy is shown to perform better both in objective and subjective measures for lesser computation, and complements the framework of image denoising.
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
IEEE signal processing letters
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