Abstract
With the continuous innovation of optical remote sensing technology and the increasing demand for spatial information, satellite videos, which can provide higher spatial and temporal resolution, have been paid a lot of attention. And moving vehicles extraction in satellite videos is one of the most important tasks. By analyzing the shortcomings of current satellite video moving vehicles extraction algorithms, and combining with the characteristics of satellite videos and moving vehicles, this paper proposes an algorithm to extract moving vehicles in satellite videos, that some vehicles are firstly separated from the background by using image extreme points and mean differences, and then the moving vehicles are extracted by joint detection of inter-frame vehicles motion. At the same time, based on the extracted moving vehicles, we also propose a method that can extract road masks by using only three frames. Finally, we use Jilin-1 satellite video data to prove the proposed methods in the experiment. And also this paper has compared the propose methods with another two algorithms, where the results show that the proposed methods greatly improve the accuracy and quality of moving vehicles detection in satellite videos.
Highlights
Compared with traditional optical remote sensing images, satellite remote sensing videos have very high spatial and temporal resolution, which can provide users with sufficient dynamic information [1], helps users to analyze the motion and instantaneous characteristics of targets more accurately [2]
In order to solve the above problems, this paper proposes an inter-frame moving vehicles detection algorithm based on images extreme points and mean differences (EPAMD)
The inter-frame moving vehicles extraction algorithm based on image extreme points and mean differences is proposed in this paper mainly includes the following steps: 1) Preprocessing of satellite video frames; 2) Extracting the complete images of vehicles by using extreme points and mean differences; 3) Eliminating the false alarm vehicles by using inter-frame joint moving vehicles detection; 4) Extracting the road masks by moving vehicles difference images
Summary
Compared with traditional optical remote sensing images, satellite remote sensing videos have very high spatial and temporal resolution, which can provide users with sufficient dynamic information [1], helps users to analyze the motion and instantaneous characteristics of targets more accurately [2]. In order to solve the above problems, this paper proposes an inter-frame moving vehicles detection algorithm based on images extreme points and mean differences (EPAMD). This method does extract complete vehicle images by using the extreme points and mean filtering of the images, effectively recognize the moving vehicles by inter-frame joint motion detection, and automatically establish the mask of the moving vehicle area by using only three frames. The proposed method effectively improves the accuracy and reduces false alarm rate and missing rate for extract moving vehicles in satellite videos
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