Abstract
A successful solution to solve an impulse noise is to use median filtration proposed by John Tuke in 1971 for the analysis of economic processes. It should be noticed that median filtration is a heuristic processing method, its algorithm is not a mathematical solution to a strictly formulated problem. Therefore, the researchers pay much attention to the analysis of the image effectiveness processing on its basis and comparison with other methods. When applying a median filter, each image pixel is sequentially processed. For median filtration, a two-dimensional window (filter aperture) is used, usually has a central symmetry, with its center located at the current filtration point. The dimensions of the aperture are among the parameters that are optimized in the process of analyzing the algorithm efficiency. Image pixels, that appear within the window, form a working sample of the current step. However median filtering smoothens the image borders to a lesser degree than any linear filtering. The mechanism of this phenomenon is very simple and is as follows. Assume that the filter aperture is near the boundary separating the light and image's dark areas, with its center located in the dark area. Then, most likely, the work sample will contain more elements with small brightness values, and, consequently, the median will be among those elements of the work sample that match this area of the image. The situation changes to the opposite, if the aperture center is shifted to the region of higher brightness. But this means the presence of sensitivity in the median filter to brightness variations.
Highlights
All color spaces can be listed from the RGB space that can be obtained from the camera or scanner
RGB space is well suited for computer graphics, because it uses these three components for color formation [2]
RGB space is not very effective when it comes to real images
Summary
When processing images in RGB space, it is not always convenient to perform any pixel conversion, because, in this case, it will be necessary to list all three values of the RGB component and write back This greatly reduces the performance of various image processing algorithms. For these and other reasons, many video standards use brightness and two signals that carry information about the red and blue components of the signal, as a color model other than RGB. In [9] was performed developed an Image Filtering and Labelling Assistant (IFLA) system to expedite the most time-consuming portion of this process This system supplies object-marked images to help researchers identify and label those that are useful. The objective of article is the process of a median image filtering for in computer systems and special purpose networks
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