Multi-focusing image fusion method utilizing core Fisher classification and redundant wavelet transformation

Abstract

The invention discloses a multi-focusing image fusion method utilizing core Fisher classification and redundant wavelet transformation. The method comprises the following steps: firstly, carrying out image block segmentation on source images and calculating definition characteristics of each image block; secondly, taking part of areas of the source images as a training sample and obtaining various parameters of a core Fisher classifier after training; thirdly, utilizing the known core Fisher classifier to obtain preliminary fusion images; and finally, utilizing redundant wavelet transformation and space correlation coefficients to carry out fusion processing on the image blocks positioned at the junction of the clear and fuzzy areas of the source images to obtain final fusion images. The invention has better image fusion performance, does not have obvious blocking artifacts and artifacts in fusion results, obtains better compromise between the effective enhancement of the image fusion quality and the reduction of the calculation quantity and can be used in the subsequent image processing and display. When wavelet decomposition layers with less number are adopted, the invention is more suitable for an occasion with higher real-time requirement.

Description

technical field [0001] The invention belongs to the field of image fusion, and in particular relates to a multi-focus image fusion method. The method utilizes kernel Fisher classification and redundant wavelet transform to fuse images with different focus scenes in the same scene to obtain a clear image that is focused everywhere. Background technique [0002] Image fusion is one of the current research hotspots in the field of image processing, and it has been widely used in remote sensing, machine vision, medicine, military, judicial and manufacturing fields. When an image sensor such as CCD or CMOS is used to acquire images, due to the depth of field of the lens, the scene located on the focal plane can be clearly projected on the image, while the scenes at other positions are blurred to varying degrees on the image. An image that is focused everywhere is a prerequisite for many subsequent processing. The main method to solve this problem is multi-focus image fusion techn...

AI Technical Summary

Problems solved by technology

There are also literatures that use discrete cosine transform to fuse the image blocks located at the junction of the clear and blurred areas of the source image, but this method requires the use of support vector machines for two classifications, and the fusion effect of discrete cosine transform is compared to that based on multi-resolution There is still a certain gap in the fusion method of analysis

There are also fusion methods proposed in some literatures that take multi-resolution coefficients as the research object, and the calculation amount is relatively large.

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