Method for fusing images based on beamlet and wavelet transform

Abstract

The invention discloses an image fusion method combining wavelet and beamlet transform, and overcomes the defect of the fuzziness of image edges and detail positions of a wavelet-based image fusion method in the prior art. The method is implemented by the following steps of: (1) inputting a source image; (2) performing wavelet decomposition; (3) performing low-frequency sub-band coefficient fusion; (4) extracting an image edge; (5) calculating edge density and a difference value; (6) performing high-frequency coefficient fusion; (7) performing consistency verification; (8) reconstructing an image; and (8) outputting a fused image. By the method, the edge information of the image is extracted effectively by utilizing beamlet transform, and the edge information is participated into the image fusion, the interference of a noise to a fusion result is reduced, and finally the fusion image with more obvious edge detail features is obtained.

Description

technical field [0001] The present invention belongs to the field of image processing technology, and further relates to remote sensing applications. In the field of medical diagnosis, a multi-source image fusion method based on Beamlet transform and wavelet transform can be applied to multi-focus image fusion, infrared visible light image fusion and noise-containing image fusion. Obtain a composite image that contains salient information from each source image. The invention can improve the accuracy of classification when used in the remote sensing application field, and can provide clear and high-quality images for more accurate medical diagnosis in the field of medical diagnosis, especially for tumor location and recognition. Background technique [0002] In the field of remote sensing applications and medical diagnosis, in order to obtain a more comprehensive, clearer, and more distinctive image of a certain scene or a certain part of the human body, a multi-source image...

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Problems solved by technology

Because of the directionality and non-redundancy of the wavelet transform, this patented technology can obtain a good fusion effect, but this method cannot capture the linear singular information of the image well when dealing with high-frequency coefficients. There is a certain fuzzy problem in the edge detail information, which is not conducive to the classification of remote sensing images and the correct diagnosis of medical treatment

[0005] In summary, although the image fusion method based on wavelet transform can achieve better results in image clarity, wavelet transform is not very good for anisotropic images, such as edges and linear features in digital images. Therefore, a series of image processing methods based on wavelet transform, in image compression, denoising, fusion and other applications, will inevitably appear a certain degree of blurring on the edge of the image and the position of details, which will give remote sensing image classification and medical diagnosis accuracy. bad influence of sex

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