摘要
由于传统方法没有通过特征提取方法获取图像关键滤波纹理系数,导致人机交互界面图像存在增强效果不佳,非平缓区域、曲面区域等不同层次信息量不丰富的问题,为解决上述问题,设计了基于视觉感知的图形化人机交互界面分层模型。构建图像处理模型,采用边缘轮廓特征提取方法,获取关键滤波纹理系数与边缘轮廓信息分量等特征信息。使用层次分析方法对交互界面视觉传达效果进行优化。以交互界面各个区域视觉感知强度和边缘轮廓内视觉感知元素重要度为基础,建立基于视觉感知强度的图形化人机交互界面分层优化模型,并通过遗传算法求解该模型,实现图形化人机交互界面的分层优化。实验结果显示,上述模型的图像亮度增强效果更优,符合人眼视觉感知要求;信息熵始终处在较高数值,具有较好的图像融合效果,信息量丰富。
Because the traditional method does not obtain the image key filter texture coefficient through the feature extraction method, the image enhancement effect of human-computer interaction interface is poor, and the amount of information at different levels such as non flat area and surface area is not rich.Therefore, a hierarchical model of graphical human-computer interaction interface based on visual perception was designed in this work.The image processing model was established.The edge contour feature extraction method was applied to obtain the key filtering texture coefficients and the components of the edge contour information.According to the analytic hierarchy process, the visual communication effect of the interface was optimized.Based on the visual perception intensity of each area of the interface and the importance of visual perception elements in the edge contour, a hierarchical optimization model of human-computer interaction interface was founded.Meanwhile, the genetic algorithm was adopted to solve the model, achieving the hierarchical optimization of graphical human-computer interaction interface.The experimental results show that the model has excellent image brightness enhancement effect, image fusion effect, abundant information and high information entropy.
作者
谷佳
王昕兵
GU Jia;WANG Xin-bing(College of Computer Science and Engineering,Ningxia Institute of Science and Technology,Ningxia Shizuishan 753000,China;Inner Mongolia Normal University,Inner Mongolia Hohhot 010022,China)
出处
《计算机仿真》
北大核心
2021年第9期190-193,365,共5页
Computer Simulation
关键词
视觉感知
图形化
人机交互界面
分层模型
视觉传达
感知元素
Visual perception
Graphical
Human-computer interaction interface
Hierarchical model
Visual communication
Perception elements
