An Efficient Algorithm for Removing RVIN in Grayscale Images

Some studies on detection and filtering algorithms for the removal of random valued impulse noise

“…In FSWMF, each detected noisy pixel is replaced by a weighted median value of uncorrupted pixels in the filtering window [25–27]. The FSWMF is an improvement over the MF and the FSMF which provide limited restoration results.…”

“…In detection part, five algorithms, namely rank order absolute difference (ROAD) [17], rank order logarithmic difference (ROLD) [18], triangle‐based linear interpolation (TBLI) [19], adaptive switching median (ASM) [20], and measures of dispersions (MOD) [21] algorithms, are taken. In the filtering part, three filtering schemes have been considered, namely median filter (MF) [16, 22, 23], fuzzy switching median filter (FSMF) [24], and fuzzy switching weighted median filter (FSWMF) [25–27].…”

Correlation Coefficient Based Detection Algorithm for Removal of Random Valued Impulse Noise in Images

“…The fuzzy switching weighted median filter (FSWM) is utilised in the filtering stage of CCBD [24]- [26]. The FSWM filter is an improvisation over the Median restoration results [27]- [30].…”

“…These conditions are based on the Correlation Coefficients of the absolute differences of the pixels in detection window (except CP) with their Mean (µ), the Central Pixel (CP) and a predefined value explained later. The filtering stage of CCBD is based on the Fuzzy Switching Weighted Median filter (FSWM) to replace only the noisy pixels detected in the detection stage while leaving noise free pixels unaltered [24]- [26].…”