학술논문
Research on Graphic Design Image Processing Technology Based on Newton's method in Photoshop
Document Type
Conference
Author
Source
2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon) Smart Technologies For Smart Nation (SmartTechCon), 2023 Second International Conference On. :710-715 Aug, 2023
Subject
Language
Abstract
The term "computer graphics and image processing technology" refers to a technology that is based on computers and makes use of software to process graphics and images in a comprehensive manner. Since its introduction, it has been the subject of extensive research and practical use, and as a result, it has steadily evolved into a fully formed and flawless technical system. Image editing, image composition, color correction, the generation of functional color effects, and other related tasks are among the primary features included in Photoshop. The title bar, the menu bar, the picture editing window, the status bar, the toolbox, the control panel, the drawing mode, the file format, the file size, the color setting, shortcut keys, and the color mode are all components of the operational interface. Studying the image processing technology used in graphic design based on NM (Newton's technique) in Photoshop platform is the focus of this research project. Using NM as a foundation, construct a graphic design image processing model. in order to make the global convergence better and reduce the goal function as much as possible. To verify that the goal function is moving in the desired direction, the modified global criterion of NM is applied. According to the findings, the new and improved algorithm has a running time that is 3.67 percent and 2.25% less than that of the NM and the inexact Newton method respectively. The root-mean-square error of the reconstructed image of the cross-section with a diameter of 19mm is controlled to be approximately 5.03%. This error decreases as the amount of Gaussian noise increases. Even if there is significant interference from Gaussian noise when the algorithm reconstructs sections of varying diameters, the quality of the reconstructed image of the improved NM has only a little amount of impact on the reconstructed image.