Iterative Fusion Based on Amplitude Minimization of Orthogonal Spatial Component and Spectral Error

Fusion of Multispectral (MS) and Panchromatic (Pan) images is known as pansharpening is a process which increases spatial resolution MS image by injecting high-frequency spatial information of Pan image. There is no pansharpening method that excellent performance on various data set, and usually its performance depends on the data set. So different pansharpening approach appear in this field. A new method is proposed that MS image and Pan image is fused iteratively in this article. The component of Pan, that orthogonal to MS, was considered as details. Because this component contains low-frequency information, spectral distortion occurs. So, a spectral error correction is used in this algorithm. Two data sets are used for evaluation and comparison to state of the art methods. The proposed method successes in visual analysis and quantity evaluation rather than other methods.