Abstract: To resist the noises and improve the quality of the fusion image,a new framework of simultaneous denoising during the image fusion is proposed.Based on the denoising framework,an image fusion framework based on Principal Component Analysis(PCA) is adopted.PCA is first applied to the source images.Then approximate images are acquired after subsampling the image reconstructed with the first-n components;the difference between current and the previous level approximate images is computed to construct a detail image.In the end,the last approximate image and all detail images are merged in form a new fused image.Embedding this fusion framework in the Total Variation model,a new framework that can fuse and denoise images simultaneously is formed.The experimental results demonstrate that this framework not only has good performance in image fusion of the same resolution,but also retain the spectral information and space information in the fusion of panchromatic and multi-spectral images.Additionally,it can restrain noises in the source images.