Different-source test image calibration method of image matching system

Abstract

The invention relates to a different-source test image calibration method of an image matching system, comprising the following steps: establishing a similar feature index candidate set of visible-light image and infrared image sequences; using a grey correlation analysis method to measure the similarity between the features in a different-source image candidate set, performing correlation degree sorting on the similar feature index candidate set on the basis, and selecting similar feature vectors; selecting different parameters according to the threshold parameter of an edge feature extraction algorithm based on a Canny operator, calculating and dividing feature value combinations, and forming a calibration test pilot scheme; and making a statistic analysis of the matching rate of a photoelectric imaging matching system to visible-light images and infrared images, performing grading based on a matching rate result output by an infrared image, and calibrating the feature value range of a corresponding visible-light image. Through the method, the matching system can be tested and evaluated through use of a calibrated visible-light image when working in an unknown environment, and therefore, the image matching system can complete the task smoothly.

Description

technical field [0001] The invention relates to the technical field of performance evaluation of an image processing system, in particular to a heterogeneous test image calibration method for an image matching system. Background technique [0002] In recent years, the image processing system has developed rapidly. Along with the proposal and improvement of a large number of algorithms, many scholars have used different image databases to analyze and test various processing algorithms. However, if the image processing system works in an unknown environment, it is still The normal realization of system functions cannot be guaranteed, especially under the condition that it is difficult to obtain test images of the same source scene. If images from other systems can be used to achieve the purpose of evaluation and testing, this is of great significance to the evaluation of image processing systems and the optimization of system functions . [0003] When analyzing and evaluating...

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Problems solved by technology

However, in an actual unknown environment, it is difficult to obtain homogeneous infrared image sequences, and it is very easy to obtain heterogeneous images of visible light, such as satellite images and aerial images. If the visible light images in an unknown environment can be used as test image sequences , to complete the test and evaluation of the image matching system, which requires the calibration of the correlation between the visible light image and the infrared image. From the related research results described above, the analysis of heterogeneous images is only a simple comparison of grayscale, features, etc. Correlation information, not related to the performance index of the matching system, is not suitable for the test and evaluation of the matching system, and the calibration method suitable for the test and evaluation of heterogeneous images has not yet been published.

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