Multi-focus image fusion method based on light field imaging

Abstract

The invention discloses a multi-focus image fusion method based on light field imaging, and the method comprises the steps: firstly obtaining a sub-aperture image of a light field image, building a refocusing model through the position relation among a main lens, a micro-lens array, a sensor and an imaging plane of a light field camera, and deducing a refocusing coefficient through the triangularrelation between a line and a plane; respectively focusing different targets in the image to the highest definition by adjusting a refocusing coefficient; dividing the refocusing image into a plurality of parts by using an image definition evaluation function, namely a Tengrad evaluation function, and establishing a mask according to the divided parts so as to represent a fusion position; and fusing the processed images by using a Laplace pyramid fusion algorithm. According to the method, it can be guaranteed that the aircraft can obtain the clewest feature information of different non-cooperative targets, interference brought by background transformation to subsequent image processing work is reduced, and the requirement of a guidance system for accuracy can be better met.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image fusion method. Background technique [0002] Image guidance has become one of the commonly used guidance methods in precision guidance systems due to its advantages of rich information, strong real-time performance, and high guidance accuracy, and has been widely used in the fields of aviation and aerospace. The camera installed at the seeker acquires target information in real time, and analyzes and processes the corresponding image sequence, so as to calculate the corresponding position information of the tracking target in the actual background. At present, most image guidance systems use monocular cameras, which have a simple structure and low cost, but because they can only capture two-dimensional images, a large amount of available light depth information is discarded; and when facing multiple non-cooperative targets , the traditional mode of ...

AI Technical Summary

Problems solved by technology

At present, most image guidance systems use monocular cameras, which have a simple structure and low cost, but because they can only capture two-dimensional images, a large amount of available light depth information is discarded; and when facing multiple non-cooperative targets , the traditional mode of focusing first and then taking pictures makes it impossible for the monocular camera to focus multiple targets to the correct depth in one image, resulting in the loss of target information and failing to meet the accuracy requirements in the guidance process. The image of the focal depth will make the subsequent image processing steps more complicated, which cannot meet the real-time requirements of the guidance; and multiple images will cause a large change in the relative information between multiple non-cooperative targets, resulting in subsequent data processing. The workload increases, which limit the development of image guidance

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