Hyperspectral change detection by using IR-MAD and synthetic image fusion

We propose a modified IR-MAD based on the generation of synthetically fused images in order to minimize the effect of change detection results corresponding to noise and feature reduction. Synthetically fused hyperspectral images were first generated using a cross-sharpening algorithm. MAD variates according to each pair of synthetically fused images were then calculated to reduce the influence of data noise in the hyperspectral image. In particular, we applied the integration of MAD variates in this study. To evaluate the performance of our algorithm, we constructed a hyperspectral dataset using the Hyperion sensor and analyzed the data noise and bands of principal components.