计算机仿真2024,Vol.41Issue(11) :286-290.

古建筑全景AI图像双角度偏振去雾仿真

Simulation of Dual Angle Polarization Defogging in AI Images of Ancient Architecture Panorama

李营 许晓政
计算机仿真2024,Vol.41Issue(11) :286-290.

古建筑全景AI图像双角度偏振去雾仿真

Simulation of Dual Angle Polarization Defogging in AI Images of Ancient Architecture Panorama

李营 1许晓政1
扫码查看

作者信息

  • 1. 沈阳理工大学,辽宁 沈阳 110159
  • 折叠

摘要

由于古建筑全景AI图像受光照条件实时变化影响,在复杂纹理和高对比度区域,存在着多种密度和颜色的雾气,若不能及时提取图像的偏振特征,会直接降低图像的去雾效果.为此,提出古建筑全景AI图像双角度偏振去雾仿真.对获取的古建筑原始图像实施去噪处理,提升图像质量,建立图像大气散射模型;根据模型获取建筑图像双角度偏振图像,提取图像偏振特征,划分图像天空区域;采用暗通道先验原理获取图像无穷远大气光强,结合上述建立的大气散射模型,实现古建筑全景AI图像的去雾增强.实验结果表明,上述方法开展图像去雾时,去雾效果好、性能高.

Abstract

Currently,the panoramic AI image of ancient architecture is affected by real-time changes in lighting conditions.In complex textures and high-contrast areas,there are various fogs with different densities and colors.If the polarization features of images cannot be extracted in time,the dehazing effect of the image will be directly re-duced.To address this issue,a dual-angle polarization defogging simulation for panoramic AI images of ancient archi-tecture was proposed.At first,the original image of ancient architecture was denoised to improve image quality.And then,an atmospheric scattering model was built.Based on the model,the dual-angle polarization image of ancient ar-chitecture was obtained.Meanwhile,the polarization features of the image were extracted.The sky region of the image was segmented.Moreover,the dark channel prior principle was used to calculate the infinite atmospheric light intensity of the image.Combined with the atmospheric scattering model,the defogging enhancement of panoramic AI images of ancient architecture was realized.Experimental results show that the proposed method has good dehazing effect and high performance.

关键词

古建筑全景图像/双角度/偏振去雾算法/图像去噪/大气散射模型

Key words

Panoramic image of ancient architecture/Dual angle/Polarization defogging algorithm/Image denoising/Atmospheric scattering model

引用本文复制引用

出版年

2024
计算机仿真
中国航天科工集团公司第十七研究所

计算机仿真

CSTPCD
影响因子:0.518
ISSN:1006-9348
段落导航相关论文