Identification and Reduction Optical Noise in Optical Imaging System

Abstract The optical imaging system has many problems, such as noise. Therefore, the challenge is to design algorithms to reduce or eliminate visual noise in such optical systems. In this study, there are several steps to identify and reduce noise. First, we determine the type of noise. Then, the median smoothing, Winner, Frost, Kuan and Lee algorithms are applied to the 3x3, 5x5 and 7x7 sliding windows. The histogram algorithm is used to recognize the types of noise, which are divided into additive and multiplicative noise. The image quality after smoothing is evaluated using statistical criteria such as mean square error (MSE), signal-to-noise ratio (SNR), normalized absolute error (NAE) and maximum signal-to-noise ratio (SNR). The results show the type of noise in the images. The noise is reduced by increasing the sliding window.