Bidirectional iteration optimization based image integrating method

Abstract

The invention provides a bidirectional iteration optimization based image integrating method, comprising the following steps: firstly, inputting already captured visible light and infrared images, computed tomoscaning medical science images and magnetic resonance medical science images into a computer; secondly, processing the visible light and infrared images, the computed tomoscaning medical science images and the magnetic resonance medical science images to calculate correlation matrixes and distance matrixes among the original images and to further set iteration step lengths; thirdly, seeking constrained conditions for iteration based on the image integration determining standards; obtaining an optimized objective function through the variables from the second step and the third step as well as the constrained conditions to realize images after the integration process; With the adoption of the above steps, the bidirectional iteration optimization based image integrating method is capable of achieving good visual effects on the integration of both visible light and infrared images and medical images. Further, with the method, more image information can be maintained in the process of integration; practical problems are properly handled; therefore, the method promises wide use in the market.

Description

technical field [0001] The invention provides an image fusion method based on bidirectional iterative optimization, in particular relates to a digital image processing technology for fusion of visible light and infrared images and medical images, and belongs to the technical field of digital image processing. Background technique [0002] With the development of sensor technology, a single visible light mode has gradually developed into multiple sensor modes. A single image sensor is often not able to extract enough information from a scene, so that it is difficult or even impossible to obtain a comprehensive description of a scene independently. This requires the study of multi-source image fusion. Image fusion can collaboratively utilize multiple sensor image information of the same scene to output a fused image that is more suitable for human visual perception or computer further processing and analysis. It can significantly improve the shortcomings of a single sensor, ...

AI Technical Summary

Problems solved by technology

However, the wavelet transform fusion algorithm has great restrictions on the selection of the window size of the transformed area in image fusion, which leads to a relatively small application range of a wavelet transform fusion algorithm

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