Image fusion algorithm based on texture features

Abstract

The invention relates to the technical field of image processing, in particular to an image fusion algorithm based on textural features, which comprises the following steps: S1, judging whether an image acquired by a visible light sensor needs enhancement processing or not, performing enhancement processing if the light is dark, and otherwise, not performing enhancement processing; s2, acquiring abase layer of the image obtained in the step S1; s3, subtracting the base layer image from the original image to obtain a detail layer of a bright pixel, similarly, subtracting the original image from the base layer image to obtain a detail layer of a dark pixel, and if the image is an invisible light image, removing halo in the detail image by using halo edges to obtain a final detail image after halo removal; s4, fusing the base layers of the images acquired by the sensors in a weighted manner; and S5, performing weighted addition fusion on the base layer fusion image obtained in the step S4 and a bright pixel detail layer, and performing weighted subtraction fusion on the fused image and a dark detail layer to obtain a final fusion image. The algorithm provided by the invention can clearly reflect the position and scene details of the object.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image fusion algorithm based on texture features. Background technique [0002] Different image acquisition sensors have different functions. Just like human senses, the combination of visual senses and auditory senses can allow our brains to better understand this colorful world. The same is true for image information. The appearance of some targets is often accompanied by fever. , the image collected by the infrared sensor mainly reflects the temperature and radiation difference of the scene, and will not be affected by the complex external environment, so the position and outline of the heating object in the image can be quickly located. Poor Unable to obtain the distribution information of the surrounding environment of the target Poor visibility, unable to provide detailed information of the image. The image collected by the visible light sensor is more prominen...

AI Technical Summary

Problems solved by technology

These algorithms have proved the important position of multi-scale decomposition method in image fusion technology, but the fused image obtained by using multi-scale changes has halos and artifacts, and the multi-scale decomposition method is in a dilemma in decomposing the number of image space layers , in order to ensure rich texture details after image fusion, the number of decomposition layers needs to be as many as possible, but when there are too many layers, the coefficient of the low-pass band layer in image fusion will affect most of the fusion pixel values, in order to balance the two relationship often reduces the robustness of such algorithms

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