access icon free Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images

In this study, a combination of adaptive vector median filter (VMF) and weighted mean filter is proposed for removal of high-density impulse noise from colour images. In the proposed filtering scheme, the noisy and non-noisy pixels are classified based on the non-causal linear prediction error. For a noisy pixel, the adaptive VMF is processed over the pixel 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 experiments have been carried out on a large database for different classes of images, and the performance is measured in terms of peak signal-to-noise ratio, mean squared error, structural similarity and feature similarity index. It is observed from the experiments that the proposed filter outperforms (∼1.5 to 6 dB improvement) some of the existing noise removal techniques not only at low density impulse noise but also at high-density impulse noise.

Inspec keywords: adaptive filters; image colour analysis; mean square error methods

Other keywords: noncausal linear prediction error; adaptive vector median filter; colour images; structural similarity; high-density impulse noise removal; VMF; peak signal-to-noise ratio; weighted mean filter; mean squared error; feature similarity index

Subjects: Interpolation and function approximation (numerical analysis); Optical, image and video signal processing; Filtering methods in signal processing; Computer vision and image processing techniques; Interpolation and function approximation (numerical analysis)

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