A new approach for high density saturated impulse noise removal using decision-based coupled window median filter

An adaptive dynamically weighted median filter for impulse noise removal

“…SAMF among conventional methods performs well for low-density noise; however, for higher densities, it provides artifacts along edges. For 90% noise density, AMF and AWMF fail to remove noise, whereas SAMF, Bhadouria [20], and Bhateja [21] restore all noisy pixels, however, at the cost of blurring along edges. The proposed method not only preserves edges for low density of noise but also performs very well for noise density as high as 90%.…”

“…If 9 × 9 window surrounding noisy pixel does not have any known noise-free pixel, it replaces the noisy pixel with previously processed or previous noise-free pixel. Bhadouria et al [21] proposed a median-based method that extends the window up to maximum allowable size of 9 × 9 when there is no noisefree pixel in the window. If 9 × 9 window does not have noise-free pixels, it replaces the corrupted pixel by mean of all pixels in 3 × 3 window.…”

“…Thresholds given in Table 3 Figure 6 shows the set of images used for comparisons of algorithms. Performance evaluation was made on the basis of comparison of peak signal-to-noise ratio (PSNR) and mean structural similarity (MSSIM) of adaptive DWMF with methods proposed by adaptive median filter (AMF), adaptive weighted median filter (AWMF), Ibrahim et al [19] (AdFuz), Bhadouria [21], and Bhateja et al [20]. [20].…”

“…e SAMF. f Bhadouria [21]. g Proposed ADWMF Tables 4, 5, and 6 show the PSNR comparisons of proposed ADWMF with conventional methods for 30, 50, and 90% noise densities respectively.…”

Adaptive Kuwahara filter

“…Nonlinear edge preserving smoothing filters have been an actively researched continuously for decades. Worth mentioning is the articles [10][11][12][13][14][15] where authors present various approaches to the problem of edge preserving smoothing filters.…”