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Analysis of Different Filter Techniques for Image Denoising
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 52 |
| Year of Publication: 2023 |
| Authors: Aziz Makandar, Shilpa Kaman |
10.5120/ijca2023922647
|
Aziz Makandar, Shilpa Kaman . Analysis of Different Filter Techniques for Image Denoising. International Journal of Computer Applications. 184, 52 ( Mar 2023), 21-28. DOI=10.5120/ijca2023922647
Abstract
Images are very important source in research field as it is easier to convey information through them. There are several resources available to generate high quality images, but presence of noise can degrade these images. Hence image denoising is one of the crucial preprocessing steps in digital image processing. This paper is an attempt to study the effect of different noise types on images and how efficiently denoising techniques can reduce noise. Gaussian noise, poisson noise, salt & pepper noise and speckle noises are the most commonly occurring noise types which are considered to conduct experiments with gray scale images. Denoising techniques applied here are gaussian filter, median filter, wiener filter, bilateral filter, non-local means and bm3d. Results of different noise used on gray scale images compared with the help of quantitative and qualitative performance parameters such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM).
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