Three Stage Weighted-Mean Filter Using Euclidean Distance

Soni M.; Arya K.V.; Garg B.; Petrlik I. · Lecture Notes in Networks and Systems (2023) · DOI: 10.1007/978-981-99-1912-3_24

Resumen

This paper presents a three-stage weighted-mean (TSWM) filter to restore digital images corrupted by high noise density impulsive noise. The proposed filter evaluates the weighted mean of non-noisy pixels (NFP) in 3 × 3 or 5 × 5 grid where the respective weights taken are proportional to their euclidean distance from the center pixel. The first step functions as a pre-processing step where the noisy pixels with the highest information or least uncertainty are denoised first using the two adjacent pixels in a straight line. And in the third stage, edge cases such as corners and boundaries are handled. The performance comparison of this algorithm is done using a 512 × 512 grey-scale Lena image. The experiment results show on an average increment of 2.54 dB and 0.15 dB of Peak signal to noise ratio for high (10% to 90%) and extremely high (90% to 98%) noise densities over popular denoising filters.

Instituciones: Universidad Nacional Federico Villarreal