An Adaptive Non-linear Statistical Salt-and-Pepper Noise Removal Algorithm using Interquartile Range

Halder, Amiya

doi:10.5565/rev/elcvia.1145

Cited by 3 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…en it is subjected to denoising by using the hardthresholding algorithm [24]. By using inverse wavelet transforms and aligning the patches correctly, the denoised image is reconstructed [25]. is method proves to be effective when the noise variance is low and the performance degrades as the noise level in the image increases and hence artifacts are introduced into the denoised image [26].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Effective Edge-Based Image Denoising Algorithm

Kumar¹,

Kumar²,

Naik³

et al. 2022

Scientific Programming

View full text Add to dashboard Cite

This article proposes an edge-based denoising algorithm to restore the original image, which is highly degraded by the salt and pepper noise. Most of the existing image denoising algorithms consider edge as a noise. Here, the proposed algorithm can set out to resolve this ambiguity. The concept of directional filters is being used to delineate the edges from noise. The proposed algorithm performance is tested for different noise densities ranging from 5% to 90% on both the greyscale and colour images. It is compared with the current state of art techniques using several performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) values, and image enhancement factor (IEF). The results showed that the proposed algorithm has achieved an improvement of 60% over the state of art techniques.

show abstract

Section: Literature Reviewmentioning

confidence: 99%