Noise in Digital Image Processing: A Review Study

We are awash with images. The quality of an image is greatly impacted by image noise, making it difficult to extract, analyze, recognize, and make quantitative measurements of features. During the image capture, coding, transmission, and processing stages, noise is always present in digital images. Robotics, education, biometrics, biomedical imaging, medical imaging, remote sensing, security, and surveillance are just a few fields where image processing needs to be without noise. Digital image noise removal is a highly challenging technique without understanding the kind of noise. Many techniques are suggested for noise removing and restoring the original image. The current paper provided an analysis of recent studies on the recognition and removal of noises published in recent years (2017–2022) to help determine the best strategy and provide resources for academics to comprehend the present methods and strategies in this area. Ultimately, new and more effective algorithms for identifying and removing noise from the images may be developed. This study aims to highlight the effect of noise on image processing, unfortunately, noise removal algorithms are still used inaccurately due to the lack of a mechanism to determine the type of noise in the image and the appropriate type of algorithm to remove this type of noise, so this study will provide information helps the researchers to address the problem of noise in the image.