Description: Noise estimation is a fundamental process in the field of image quality, referring to the evaluation and quantification of the amount of noise present in a digital image. Noise in images can be caused by various factors, such as inadequate lighting conditions, sensor sensitivity, or interference during image capture. This noise manifests as random variations in pixel values, which can negatively affect the clarity and accuracy of the image. Noise estimation allows for the identification and measurement of these variations, which is crucial for applying noise reduction techniques and improving the visual quality of images. There are different methods to perform this estimation, which may include statistical analysis of pixels, specific noise models, and machine learning algorithms. The accuracy of noise estimation is vital, as it influences the effectiveness of restoration and enhancement processes, as well as data interpretation in scientific and technical applications. In summary, noise estimation is an essential component in image processing and computer vision, aiming to optimize visual quality and the utility of digital images across various applications.
