The quality assessment of fusion effect for remote sensing image

With the rapid development of remote sensing technology, the way of obtaining remote sensing data is becoming more abundant. Images on the same area obtained by different sensor are increasing and form the multi-temporal and multi-resolution image sequence. How to integrate various types of these images and improve the using effectiveness has become bottlenecks in application. Data fusion technology is an effective means to solve this problem. The fusion techniques have been developed quickly in recent years, a hot research topic. At present, there are many image fusion methods which are widely used by the mainstream professional softwares. And the pixel level image fusion technique is relatively more mature, including IHS transform, PCA transform, HPF transform and wavelet transform and so on. These four methods will be discussed systematically in this paper. Compared to relatively mature fusion technique, the quality assessment technique of image is imperfect. In the paper, I choose TM and SPOTS images as experiment data, employ four different fusion methods, use standard deviation, entropy, average gradient, correlation coefficient as quality assessment criteria in order to choose the suitable method for our merging purpose.