Noise Models in Digital Image Processing

Noise Models in Digital Image Processing

Author Name : Manikant Raddi, Maski Sriharsha, Pramod HV, Nithin Babu, Chrispin Jiji

ABSTRACT Digital images contain a wealth of information and are integral to numerous aspects of daily life. For this reason, it is essential that images maintain accuracy and clarity. However, during processes such as image acquisition, coding, transmission, and processing, images often become degraded due to noise. Noise interference alters the original pixel values, causing distortion in significant parts of the image. Consequently, noise removal is critical and necessitates an understanding of the type of noise, its effects, and its causes. This paper provides an overview of various types of noise commonly encountered in digital images. Noise is typically introduced during image acquisition, coding, transmission, or processing stages. Eliminating noise from digital images is highly challenging without prior knowledge of the noise model. Therefore, reviewing noise models is an essential step in the development and application of image denoising techniques. In this work, we offer a concise review of different noise models, which can be classified based on their sources. By analyzing their origins, we present a comprehensive and systematic study of noise models prevalent in digital images. This serves as a foundation for better understanding and addressing the challenges associated with image denoising.