  The most significant problem may be undesirable effects for the spectral
signatures of fused images as well as the benefits of using fused images mostly
compared to their source images were acquired at the same time by one sensor.
They may or may not be suitable for the fusion of other images. It becomes
therefore increasingly important to investigate techniques that allow
multi-sensor, multi-date image fusion to make final conclusions can be drawn on
the most suitable method of fusion. So, In this study we present a new method
Segmentation Fusion method (SF) for remotely sensed images is presented by
considering the physical characteristics of sensors, which uses a feature level
processing paradigm. In a particularly, attempts to test the proposed method
performance on 10 multi-sensor images and comparing it with different fusion
techniques for estimating the quality and degree of information improvement
quantitatively by using various spatial and spectral metrics.
