Published Paper Details:

In the proposed method, the intensity component is obtained adaptively from the up-sampled MS image at first. Different from traditional IHS-based methods, we subsequently propose a multi-scale guided filter strategy to filter the PAN image to achieve more detail information. Finally, the total detail map is injected into each band of the up-sampled MS image to obtain the fused image by a model-based algorithm, in which an improved injection gains approach is proposed to control the quantity of the injected detail information. Among these, wavelet transform becomes an important aspect of image fusion research with the merits of multi-scale and multi-resolution. In an algorithm of multi-sensor image fusion using wavelets and Principal Component Analysis (PCA) is proposed and comparison of image fusion with different techniques based on fusion quality performance metrics is done. Multi-resolution wavelet transforms provides good localization in both spatial and frequency domains. Discrete Wavelet Transform (DWT) provides directional information in decomposition levels and contains unique information at different resolutions. Wavelets are suffered with shift variant and edges are not produced in the fused image. Stationary Wavelet Transform (SWT) solves this problem which is shift invariant. Image fusion using SWT with higher levels of decomposition provides better fusion results. Experimental results demonstrated that the proposed method can provide more spatial information and preserve more spectral information compared with several state-of-the-art fusion methods in both subjective and objective evaluations. A fast and effective image fusion method is proposed for creating a highly informative fused image through merging multiple images. The proposed method is based on a two-scale decomposition of an image into a base layer containing large scale variations in intensity, and a detail layer capturing small scale details.