Rapid matching method of multispectral images based on edge detection
A multi-spectral image, matching method technology, applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problems of unable to achieve matching, consistent field of view, poor robustness, etc., to achieve good global convergence performance, fast The effect of image matching and strong fault tolerance
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2011-04-20
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention relates to the technical field of image processing, in particular to an image matching method.
[0002] technical background
[0003] Image matching refers to identifying points with the same name between two or more images through a certain matching algorithm, and its essence is the optimal search problem using matching criteria under the condition of primitive similarity. Image matching can be mainly divided into grayscale-based matching and feature-based matching. Matching methods based on grayscale include cross-correlation registration method, Fourier method and maximum mutual information method and so on. The feature-based matching method is to extract the features of the image, including feature points, target edges, and terrain feature lines (such as ridge-valley lines, rivers, roads, room angles), etc., and use these features to calculate spatial transformation parameters. These matching methods are not suitable for all image ...
Examples
Embodiment Construction
[0045] see figure 1 It is a flowchart of a basic embodiment of the multispectral image fast matching method disclosed in the present invention, and the method includes the following steps:
[0046] A. Obtain the grayscale image of the multispectral image of the same scene at any field of view;
[0047] B. Filter and denoise each grayscale image obtained in step A to obtain a smooth grayscale image;
[0048] C, carry out edge extraction to the smooth grayscale image that B step obtains;
[0049] D. Use a preset rectangular window to filter out some edge points of the image obtained in step C to obtain an edge discrete grayscale bitmap;
[0050] E. Set the matching parameters to be solved, and use the particle swarm optimization method to optimize and solve the matching parameters to obtain the best matching effect.
[0051] Each step will be further described in detail below.
[0052] Step A: Obtain the grayscale image of the multispectral image of the same scene at any fie...