基于PCA和DWT变换的不同重采样方法图像融合效果评价对比分析  

Comparison and Evaluation of Image Fusion Based on PCA and DWT with Different Resampling Methods

作　　者：刘姝岑 Liu Shucen(Map Institute of Yunnan Province,Kunming 650034,China)

机构地区：[1]云南省地图院,云南昆明650034

出　　处：《科学技术创新》2022年第12期70-74,共5页Scientific and Technological Innovation

摘　　要：在图像融合中,图像融合研究分析以及评价是一个重要的问题,一直以来,这个问题都没有得到很好的解决,因此找寻让融合的图像可信度更高、分辨率更高、理解性更强的方法,同时我们又需要客观的评价指标来对图像的质量进行区分。通过用主分量(PCA)变换、小波(DWT)变换的方法融合图像,并提出对融合后图像的单因素指标评价,还有综合指标评价,并对它们进行分类实验,得到结论,并且对此进行分析,哪种方式能够较好的得到并且提高影像的解译又适用于生活中的图像融合。In image fusion, the analysis and evaluation of image fusion is an important problem, which has not been well solved, so we need to find a way to make the fused image more credible, higher resolution and better understanding. At the same time, we need objective evaluation index to distinguish the quality of the image. By using the methods of Principal Component Analysis(PCA) and wavelet(DWT) transform to fuse the image, the single factor index evaluation and the synthetic index evaluation of the fused image are put forward, and the classification experiments are carried out to get the conclusion, and the analysis is carried out, which method can be better to get and improve the interpretation of images and suitable for life in the image fusion.

关 键 词：图像融合 主分量变换 小波变换 图像评价 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]