16 April 2012 Novel method for removal of multichannel impulse noise based on half-space deepest location
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Abstract
A novel method is proposed for removing impulse (random-valued and salt-and-pepper) noise from multichannel digital images based on an adapted version of the DEEPLOC algorithm introduced by A. Struyf and P. J. Rousseeuw for calculation of approximate half-space (Tukey's) deepest location (median) in multivariate case. Due to its intrinsic multivariate/multidimensional nature, the proposed method eliminates the noise simultaneously on all channels without their separation, which preserves the spectral correlation between channels in a multichannel image. Denoising results of this new nonlinear spatial domain filter applied to benchmark images outperform currently used state-of-the-art filters for impulse noise removal from multichannel images in terms of both objective effectiveness criteria [peak-signal-to-noise-ratio (PSNR), mean absolute error (MAE), and normalized color distance (NCD)] and visual quality. The proposed filter successfully preserves the edges and fine image details, and is very effective for removal of medium and heavy multichannel impulse noise.
© 2012 SPIE and IS&T
Djordje Baljozovic, Branko Kovacevic, Aleksandra Baljozovic, "Novel method for removal of multichannel impulse noise based on half-space deepest location," Journal of Electronic Imaging 21(1), 013025 (16 April 2012). https://doi.org/10.1117/1.JEI.21.1.013025 . Submission:
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