Remote sensing image fusion assessment based on SVD

Existent measures of fused image quality were analyzed to research the objective evaluation problem of remote sensing image fusion. A new approach based on the singular value decomposition (SVD) was proposed for the remote sensing image fusion assessment. This method measured the divergence of the singular value features between the source images and fused image, and calculated energy distortion of fused image from source images. By that means, effect of fusion algorithm was measured. Experiments were conducted from two aspects to confirm the idea. When the source images including SAR image, this method is more effective than the Piella-s evaluation methods and Xydeas-s evaluation methods. In the other hand, the experiments of different kinds of sensors and pixel-level fusion algorithms show that the objective evaluation appears highly consistent with the subjective evaluation. It is an effective and universal assessment method with high coherence to the subjective factors.