Infrared And Visible Image Fusion Method Based On Improved Principal Component Analysis

Image fusion is a combination of the sensors from the same or different types of two ormore images technology, to produce a more accurate, comprehensive and reliable imagedescription or explanation, so that the image is more suitable for human visual perception,or the computer’s processing tasks.With the continuous development and improvement of the CCD camera and infraredcamera imaging technology, infrared and visible image fusion application in the field ofsecurity monitoring and information navigation gradually become a hot research field ofimage fusion. Infrared and visible image fusion algorithm to achieve the requirements ofthe basic monitoring and navigation, but complex fusion algorithm fusion slow integrationof lower quality lead to poor imaging results is not efficient problem persists. So efficientexcellent for infrared and visible image fusion algorithm is the current and future period oftime within a hot spot in the field of image fusion direction. In this paper, the infrared andvisible image fusion Research and typical fusion, mainly to do the following work:First, the introduction of the concept of image fusion level image fusion, image fusionrule, the fusion step with common fusion and image fusion pretreatment.Then, we introduce the infrared and visible image fusion technology applications andtheoretical study of the current situation, listing several commonly fusion methods, as wellas the corresponding experimental data.Finally, the integration method of analysis based on principal component analysis (PCA)and PCA combined with multi-resolution decomposition method based on PCA method todo a little improvement, and the principle of image fusion take maximum signal strengthon the fusion rules. By experimental data compared with PCA and PCA-DCM, whether itis a subjective evaluation or objective evaluation, this paper improved fusion methodworks better.