Research on Image Registration of Agricultural and Forestry Aerial Photos Based on Improved DISK Algorithm
Aiming at the issues of limited feature point recognition and inaccurate feature point matching in drone-based agricultural and forestry aerial image registration algorithms,this paper proposes an improved Discrete Keypoint(DISK)algorithm.This algorithm first employs a gradient strategy DISK algorithm to effectively describe feature points;secondly,it uses a deep learning-based local feature matching method for preliminary matching;finally,the RANSAC(Random Sample Consensus)algorithm is utilized to eliminate outliers and filter the matching results.To validate the effectiveness of the algorithm,several datasets of agricultural aerial images have been selected for experimental comparison.The experimental results show that,compared to the classic SIFT and Dark feat algorithms,as well as the original DISK algorithm,the improved DISK algorithm significantly enhances matching accuracy from 41.7%to 98.9%,which fully meets the matching requirements for agricultural and forestry aerial photos.
agricultural and forestry aerial photosgradient strategylocal featuresimage registrationDISK algorithm
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