EATURES OF ALGORITHMIC AND SOFTWARE TOOLS FOR FRAMING FUZZY IMAGES

Abstract

Abstract: This article examines the features of algorithmic and software tools for processing fuzzy images. The work uses three filters: CIGaussianBlur, CIUnsharpMask and CIBlendWithAlphaMask. The described filters allow you to improve image quality, reduce noise and reproduce details.The initial task is to process the blurring of images. For this, the CIGaussianBlur filter is used, which applies a Gaussian blur to the image. This blur reduces high-frequency noise and adds smoothness to the contours of objects.The second filter, CIUnsharpMask, is used to restore image details. This filter subtracts the blurred version from the original image, which allows you to highlight important details and increase the clarity of the image. The last filter, CIBlendWithAlphaMask, is used to blend two images using an alpha mask. This filter allows you to control the transparency and adjust how the images are blended. As a result, a more realistic and aesthetic image can be achieved. The article considers the principles of operation of each of the filters, gives examples of their use and describes the results obtained. Research shows that using these filters can improve the quality of blurry images, reduce noise, and sharpen details. The results of this work can be useful for use in the field of image processing, computer vision and graphic design. Using the described filters can help improve the visual characteristics of images and provide a more accurate interpretation of fuzzy data. Keywords: fuzzy images, algorithmic tools, software tools, image processing, filters.