High-Density Impulse Noise Reduction From Colour Images Using Combined Adaptive Vector Median Filter And Weighted Mean Filter
Keywords:
Denoising, VMF, WMF, Mean square error, Peak Signal to Noise Ratio, Structural Similarity Index Measure.Abstract
Image processing is carried out to improve and upgrade the quality of a noisy image. The images usually get different kinds of noises in process of receiving, coding and transmission. Denoising can be done by numerous methods like neighbourhood operations, arithmetic operations, Transforms etc. In this work, high-density impulse noise reduction on colour images can be performed by the combined effect of adaptive vector median filter (VMF) and weighted mean filter. In the proposed filtering scheme, the corrupted and good pixels are classified based on the non-causal linear prediction error (NCLPE). For a corrupted pixel, the adaptive VMF is processed on the picture element where the window size is adapted based on the availability of good pixels. Whereas, a non-noisy pixel is substituted with the weighted mean of the good pixels of the processing window. The tests have been carried out on a big database for different classes of images, and the performance is measured in terms of peak signal-to-noise ratio, mean squared error and structural similarity. It is observed that the proposed filter outperforms some of the existing noise reduction methods of impulse noise at low density as well as at high-density.
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