摘要： 为了将聚焦于不同目标对象上的多幅图像融合成一幅所有目标都清晰的图像,提出一种基于量子衍生理论的可完全重构的数字图像分解方法。该方法把归一化后的灰度图像表示成量子比特的形式,建立量子关联系统,将图像分解成若干个特征子图,考虑特征子图的含义,选择 相应的融合规则进行融合与重构,从而得到最终的融合图像。实验结果表明,与传统的平均加权法和基于小波变换的图像融合方法相比,该方法能获得较为清晰的融合图像。

关键词: 数字图像, 量子衍生, 图像分解, 图像融合, 多聚焦, 区域梯度

Abstract: In order to put gray images focused on different object into one completely clear image,this paper presents a reconfigurable decomposition method of digital image based on quantum mechanics theory,and proposes a new multi-focus image fusion algorithm.The normalized gray image is expressed as the form of quantum bit,and establishes quantum correlation system,the image is decomposed into several characteristic sub-images.According to the different meaning of characteristic sub-images,it uses different fusion rules,and is reconstructed to obtain the fusion image.Experimental results show that the method can get clearer fused images than the traditional weighted average method and the image fusion method based on wavelet transform.

Key words: digital image, quantum-inspired, image decomposition, image fusion, multi-focus, reginal gradient

中图分类号: 

• TP391.41