Improvement of digital image filtering algorithm using spline filter in Matlab environment

DOI: 10.31673/2412-9070.2020.063335

Abstract

This article is about the use of modern technology for image recovery using the example of median and spline filters. Modern approaches to solving these problems, their advantages and disadvantages are shown. Custom spline and median filters have been created to filter out noisy images. Based on the filter results, a comparison of median and spline filters was made. One of the fundamental problems of our time is the problem of visual perception. Having emerged a long time ago, it is relevant today, because the image is a natural means of communication between man and machine in any system of processing, analysis, and control. Today, the field of science and technology, which uses information processing systems using digital data, has become widespread. The basic components of such digital information conversion systems are those designed to digitally transmit natural or artificial objects that are analog information carriers. Data in digital form is used for storage, transmission, analysis, and processing in digital information processing systems. Computer graphics are divided into three main areas: visualization, image processing, and pattern recognition. Improving image quality is a priority of the system. Noise suppression is one of the most urgent and common problems in image processing. The main purpose of the improvement is to process the image so that the result is more appropriate from the point of view of the particular application. One of the main types of information systems that use digital data is radiographic systems. The main task of processing is to eliminate defects, reduce the effects of distortions and noise, to transform the image into a convenient for observation by a radiologist. Of particular importance are X-ray image processing techniques. The efficiency of making the right diagnosis, detecting in the early stages of serious illness is largely achieved by the quality of digital materials.

Keywords: spatial processing; frequency processing; matrix; image; Fourier transform; Gaussian noise; spline filtration.

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