Image fusion method based on multi-morphological sparse representation

Abstract

The invention discloses an image fusion method based on multi-morphological sparse representation. The method includes the steps of 1, extracting edge components of an infrared image by means of frequency-tuned salient region detection, and subjecting the edge components of the infrared image to spare representation by means of Curvelet basis; 2, forming a multi-morphological sparse basis by means of DWT (discrete wavelet transform) and DCT (discrete cosine transformer), and subjecting a visible light image to spare representation by means of the multi-morphological sparse basis so as to obtain spare coefficients of image smooth components and texture components; 3, fusing the edge components of the infrared image to the spare coefficients of the smooth components and texture components of the visible light image; 4, subjecting the fused sparse coefficients to inverse transform so as to obtain a final fused image. The method has the advantages that image data quantity is decreased, the edge information and texture information of the image is fully retained, and quality of the fused image is greatly improved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for performing sparse representation and fusion of infrared images and visible light images by using multi-morphic sparse bases based on the principle of morphological component analysis. Background technique [0002] Visible light images are reflection images of objects with high contrast and rich detail information, which are suitable for human observation; however, under low-illumination weather conditions, visible light images are prone to loss of detail information, and when the chromaticity difference between the target and the background is small, Easy to lose target. The infrared image is the image produced by the radiation of the object itself, which is less affected by the lighting conditions, but the contrast of the infrared image is low, and the ability to reflect the target details is relatively poor, which does not conform to the visual habits of the human e...

AI Technical Summary

Problems solved by technology

[0002] Visible light images are reflection images of objects with high contrast and rich detail information, which are suitable for human observation; however, under low-illumination weather conditions, visible light images are prone to loss of detail information, and when the chromaticity difference between the target and the background is small, easy to lose target

The infrared image is the image produced by the radiation of the object itself, which is less affected by the lighting conditions, but the contrast of the infrared image is low, and the ability to reflect the target details is relatively poor, which does not conform to the visual habits of the human eye.

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