摘要
针对当前植物景观三维图像表面点自相似性系数较低,边缘锐化效果较差的问题,提出基于色调映射和颜色特征分解的植物景观三维图像边缘锐化方法.采用稀疏线性组合方法进行植物景观三维图像的边缘轮廓特征分解,提取植物景观三维图像的边缘分块特征量;根据植物景观的表面点、细节区域进行植物景观图像超分辨率重构和模板匹配,重建植物景观图像的整体直方图分布模型,采用色调映射和颜色特征分解方法,获得植物景观三维图像边缘锐化表面点自相似性系数.仿真结果表明,该方法获得的自相似性系数较高.
In order to solve the problem of low self-similarity coefficient and poor edge sharpening effect for 3D image of plant landscape,an edge sharpening method for 3D image of plant landscape based on hue mapping and color feature decomposition was proposed.A sparse linear combination method was used to decompose the edge outline features of 3D image for plant landscape,and the features of edge blocks of 3D image for plant landscape were extracted.According to the surface points and detail areas of plant landscape,the super-resolution reconstruction and template matching of plant landscape image were carried out,and the overall histogram distribution model for plant landscape image was reconstructed.The self-similarity coefficients of surface points of sharpened edges of 3D image for plant landscape were obtained by hue mapping and color feature decomposition methods.The simulation results show that the self-similarity coefficients obtained with the as-proposed method are relatively higher.
作者
刘静霞
LIU Jing-xia(School of Architecture, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
出处
《沈阳工业大学学报》
EI
CAS
北大核心
2020年第3期298-302,共5页
Journal of Shenyang University of Technology
基金
河南省示范性虚拟仿真实验教学项目(教高【2018】991号).
关键词
植物景观
三维图像
边缘锐化
稀疏表示
自相似性
表面点
色调映射
颜色特征
plant landscape
3D image
edge sharpening
sparse representation
self-similarity
surface point
hue mapping
color feature