Таблично-алгоритмічний метод для антиаліайзингу зображення відрізків прямих

 Increasing the informativeness of computer graphics is achieved due to the formation of images that accurately reproduce the structural and visual features of the object. When forming such images, it is necessary to display graphic scenes with great detail, therefore, at this stage of the...

Full description

Saved in:
Bibliographic Details
Date:2023
Main Authors: Башков, Є.О., Курінний, М. С.
Format: Article
Language:Ukrainian
Published: Vinnytsia National Technical University 2023
Subjects:
Online Access:https://oeipt.vntu.edu.ua/index.php/oeipt/article/view/643
Tags: Add Tag
No Tags, Be the first to tag this record!
Journal Title:Optoelectronic Information-Power Technologies

Institution

Optoelectronic Information-Power Technologies
Description
Summary: Increasing the informativeness of computer graphics is achieved due to the formation of images that accurately reproduce the structural and visual features of the object. When forming such images, it is necessary to display graphic scenes with great detail, therefore, at this stage of the development of computer graphics, special attention is paid not only to the speed of forming graphic images, but also to their realism. In most modern computer graphics systems, the raster principle of image formation is used. When creating raster images, distortions occur due to the insufficient resolution of the raster. Artifacts appear on the images, one of the manifestations of which are pronounced steps or teeth on the edges of objects. The aliasing effect significantly affects the realism of the formed image, which necessitates the development of special methods and means of its elimination The tabular method of vector anti-aliasing was further developed. It is proposed to calculate the values of the evaluation function to store its values with a larger quantization step, and to calculate the intermediate ones according to the derived formula. The analysis showed that the use of the proposed approach allows reducing by 8¸17 times the amount of memory needed to calculate the pixel coverage area. The method involves hardware and software implementation and can be used in high-performance computer graphics systems.