摘要
针对KAZE算法对光照不均图像特征点提取效果不佳的问题,提出了一种基于纹理抑制改进后的KAZE图像配准算法。改进算法的主要流程如下:将纹理抑制算法嵌入到非线性扩散滤波方程中,以实现对图像更好的光照估计;对光照估计后图像的亮度分量进行自适应Gamma校正;利用改进的KAZE算法对图像进行配准。实验结果表明,改进算法相较于SIFT、SURF、KAZE算法的平均正确匹配率分别提高了48.5个百分点、22.1个百分点和20.1个百分点,查全率提高了26个百分点、5个百分点和5.5个百分点,所提算法能有效地降低误匹配,并且广泛地应用到多种处理场景中。
To solve the problem that the KAZE algorithm does not extract the feature points of the uneven illumination image,an improved KAZE image registration algorithm based on surround suppression is proposed.The main process of the improved algorithm is as follows:Firstly,the surround suppression algorithm is embedded into the nonlinear diffusion equation to achieve better illumination estimation of the image.Secondly,adaptive Gamma correction is applied to the luminance component of the image after illumination estimation.Finally,the image is registered using the improved KAZE algorithm.The experimental results show that the average correct matching rate of the improved algorithm is 48.5 percentage points,22.1 percentage points,and 20.1 percentage points higher than that of SIFT,SURF,and KAZE algorithms respectively and the recall is increased by 26 percentage points,5 percentage points,and 5.5 percentage points.The proposed algorithm can effectively reduce mismatches and is widely used in a variety of processing scenarios.
作者
刘天
曾亮
LIU Tian;ZENG Liang(College of Computer,National University of Defence Technology,Changsha 410073,China)
出处
《计算机工程与应用》
CSCD
北大核心
2020年第23期180-188,共9页
Computer Engineering and Applications
基金
国家自然科学基金(No.61272009)。
关键词
图像配准
特征检测
特征匹配
KAZE算法
纹理抑制
image registration
feature detection
feature matching
KAZE algorithm
surround suppression
