Rayleigh-Monte Carlo Method for Image Noise Detection and Elimination

Abstract

Abstract The issue of identifying areas of distortion in images is a common problem encountered in digital media processing. Traditional filtering methods often rely on setting thresholds that are dependent on the specific image being processed, leading to imprecise results. Adaptive filters have been proposed as a solution, but they are not without their technical difficulties. This paper presents a study on the effectiveness of the Rayleigh distribution method in identifying distortion areas in images. Monte Carlo estimation was used to estimate the distribution of image content, and the results showed that the Rayleigh distribution is highly efficient at identifying areas of distortion. The filtering process was then applied only to the regions with deformation, while ensuring that all other features of the image were preserved. The novelty of this study lies in the use of the Rayleigh distribution method to identify areas of distortion in images. The purpose of this study was to improve the quality of images by using a more precise filtering method that only targets distorted areas. The theoretical framework of this study is based on the application of the Rayleigh distribution method in digital media processing. The approach used in this study involved the use of Monte Carlo estimation to determine the effectiveness of the Rayleigh distribution method. The findings of this study show that the Rayleigh distribution method is highly effective in identifying areas of distortion in images, leading to higher quality images than traditional filtering methods. The research findings have practical implications for digital media processing industries, where the quality of images is paramount. By using the Rayleigh distribution method, images can be processed more efficiently, leading to improved quality and reduced processing time. Socially, improved image quality can have a positive impact on areas such as medical imaging, where accurate and high-quality images are crucial for diagnosis and treatment. Overall, this study offers an original and effective solution to the problem of identifying areas of distortion in images. By using the Rayleigh distribution method, images can be processed more precisely, leading to higher quality results. The use of Monte Carlo estimation provides a solid foundation for future research in this area.