Suppression of “salt and pepper” noise based on Youden designs
Kamel Boukerrou, LUDWIK KURZ · Information Sciences · 1998
This paper presents a new class of algorithms based on Youden designs to detect and restore edges present in an image imbedded by mixture or “salt and pepper” noise. The mixture noise consists of a uncorrelated or correlated noisy background plus uncorrelated impulsive noise. The objective is to restore pixels affected by the impulsive part of the mixture noise. The approach is to consider that these pixels have lost their true value and their estimate is obtained via the normal equation that yields the least sum of square error (LSSE). This procedure is known in the literature as “The Missing Value Approach Problem”. The estimates are introduced into the image data and an ANOVA technique based on Youden design is carried out. We introduce Youden designs which are special Symmetric Balanced Incomplete block (SBIB) designs, the pertinent statistical tests and estimates of the factor effects. We derive the estimate of the missing value for the uncorrelated noise environment as well as for the correlated one. The high level of performance of these algorithms can be evaluated visually via the input/output images and objectively via the input/output signal-to-noise ratio (SNR).