COMPARATIVE ANALYSIS OF TWO FILTERING METHODS TO ELIMINATE NOISE IN AN IMAGE OF DIFFERENT DEGREES OF NOISE

Abstract

In modern photography and video technology, any image in the process of its creation is distorted by various types of noise. There are various types of noise, but in practice, impulsive and Gaussian noise models are the most common. Attenuation of the effect of noise is achieved by filtering. At the moment, there is no universal filter that suppresses noise data at various intens ities of distortion. Therefore, an important aspect is to determine the field of application of each type of filter when suppressing noise in the image and creating a filter, consisting of a combination of different filtering methods for optimal image cleaning. The article presents a comparative analysis of median filtering and Wiener filtering to eliminate impulse and Gaussian noise in the image with different degrees of noise. For modeling, we used one image, separately distorted by impulse and separately by Gaussian noise with pixel distortion probabilities from 1% to 99% inclusive. Filtration was performed with windows equal to 3x3 and 5x5. As a result, we obtained numerical estimates of the image filtering quality based on the peak signal-to-noise ratio (PSNR). On the basis of the data obtained, the application of the investigated filters, their modifications, advantages and disadvantages were analyzed, as well as recommendations for their use were given. As a result of a comparative analysis of the studied types of filtering for noisy images, it was found that the median filter with a 3x3 window copes better with image cleaning from low-intensity impulse noise and with a 5x5 window - with image cleaning with an average noise intensity. Also, the median filter does a better job of filtering out Waussian noise at its medium and high rms deviations. The Wiener filter with 3x3 and 5x5 windows better fi lters Gaussian noise at small values of its root-mean-square deviation. Also, the Wiener filter copes better with impulse noise with relatively high noise power.