Remote Sensing Image Fusion Method Based On Pixel-level

In recent years, multi-sensor image fusion (information fusion) has attracted many attentions in remote sensing area and image project area. What the multi-resource remotely-sensed image fusion technique study is how to use the advantages of image originating from different kinds of sensors synthetically, and achieve a new image with more precise, more abundant in formation through a certain algorithm. Remote-sensing image fusion becomes in dispensable in image Processing and understanding as well as many important military and civil applications. At the same time, there provides not only a challenge, but also a good chance for the application of remotely-sensed image fusion technique.This paper focuses on image fusion between multi-spectral images and panchromatic images. We mainly pay attention to the improvement of image fusion algorithm and analyzing the application of every fusion algorithm in monitoring land utilization changes. The main content would be shown as follows.1. This paper dissertate the definition of remote sensing image fusion and its current situation at home and abroad, and then sum up the application of remote sensing image fusion technique in usually.2. This paper analysis and comparison the algorithms of image fusion that is related to the new methods such as IHS fusion, and use the best of the HIS fusion algorithm; produces the wavelet fusion and an improved methods of wavelet fusion; analysis the DCT fusion and an improved algorithm of DCT fusion.3. After analyzing many kinds of fusion methods, we carry out all of the algorithms, and do experiment to estimate these two algorithms subjectively, objectively and comprehensively.4. After give some objective evaluation criterions, this paper gives a comprehensive assessment which based on weighted and appraises experiment result using this criterion.5. The methods for extracting Information from land-use change monitoring have been studied. I select a piece of image, make an experiment to evaluate precision of extracted area to each method, and analyze the feasibility of every method systematically.