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基于图像分解增强的夜间图像拼接方法

Mengying Yan¹, Danyang Qin^1,2, Gengxin Zhang¹

¹Department of Electronic Engineering, Heilongjiang University, Harbin 150080, China.

Entropy (Basel, Switzerland)

|September 28, 2023

概括

本研究介绍了一种新的夜间图像拼接方法,使用图像分解和增强. 该技术改善了在黑暗地区的特征提取,从而为安全和自动驾驶等应用提供了更清晰的全景图像.

科学领域:

计算机视觉计算机视觉
图像处理图像处理

背景情况:

夜间图像拼接对于安全和智能驾驶至关重要,但受到不均的亮度和黑暗区域的挑战.
从黑暗区域提取结构特征是很困难的,导致幽灵和错位在拼接图像.

研究的目的:

提出一种图像分解和增强方法,以改善夜间图像拼接.
解决在黑暗的夜间环境中线路特征提取不足的问题.

主要方法:

拟议的算法将图像分解为结构和纹理层.
它增强了结构层中的发光度,并消除了纹理层.
边缘增强应用于融合图像以改善纹理细节.

主要成果:

该方法显著提高了图像质量,包括信息和对比度.
与现有的算法相比,它表现出优越的噪音抑制.
该算法有效地从处理的夜间图像中提取更多的线条特征.

结论:

图像分解和增强方法有效地克服了夜间图像拼接的挑战.
这种方法为在低光条件下创建高质量的全景图像提供了更强大的解决方案.

关键词:

边缘增强增强边缘增强功能提取特性提取图像增强图像增强图像增强夜景图像拼接拼接拼接

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