A method of target recognition in aviation airborne navigation images based on harmony search using spatial entropy

Through the harmony search method based on spatial entropy, the contrast of aviation airborne navigation images is enhanced, and the harmony search algorithm with maximum entropy is used to find the best threshold segmentation point, which solves the problem of difficulty in identifying small targets in low contrast and complex environments in the prior art, and achieves a more efficient and robust target recognition effect.

CN119205832BActive Publication Date: 2025-03-18LOONGRISE AVIONICS CO LTD
2 Cites 0 Cited by

Patent Information

Application Number
CN202411696868.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-11-26
Publication Date
2025-03-18
Estimated Expiration
2044-11-26

AI Technical Summary

Technical Problem

Existing aeronautical airborne navigation image processing technology is difficult to identify small targets in low contrast and complex environments, and has high algorithm complexity and insufficient adaptability and robustness.

Method used

The harmony search method based on spatial entropy is adopted, and the entropy value calculation and uniform distribution function mapping of image grayscale spatial distribution, combined with 2D-DCT transformation and weighting processing, the enhancement of global and local contrast is achieved. Then, using the harmonic search algorithm of maximum entropy, the optimal threshold segmentation point is found to achieve target recognition.

Benefits of technology

Improve image contrast, making the target easier to distinguish between the background, enhances the accuracy and robustness of target recognition, simplifies algorithm design, and improves adaptability and efficiency.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The present invention discloses an aviation airborne navigation image target recognition method based on spatial entropy harmony search. The method utilizes the position distribution information of the image grayscale space to calculate the image grayscale space distribution entropy value, and maps it into a uniform distribution function. The function is then processed by 2D-DCT, transform system weighting and inverse 2D-DCT linear transformation to achieve simultaneous enhancement of the global and local contrast of the original image. The method is combined with the maximum entropy harmony search algorithm. Although the method is similar to the genetic algorithm, it adopts a multi-point mating mode in the process of searching for new solutions in the field, so that the new solutions are more diverse and the possibility of the algorithm jumping out of the local optimal solution is improved.
Need to check novelty before this filing date? Find Prior Art