Study On Multi-Sensor Remote Sensing Image Fusion Based On Wavelet Technology

As one of the important aspects of image fusion, multi-sensor remote-sensing image fusion (MS-RSIF) investigates how to integrate image information from different remote sensors, and generate new data, for more complete, objective, and essential cognition of the specified target, today, multi-sensor remote-sensing image fusion becomes indispensable in image processing and understanding, along with many important military and civil applications.Summarizes pixel-level image fusion methods in this paper, analyses in the traditional spectral enhancement image fusion algorithm, the wavelet transform and the wavelet packet transform algorithm, the experimental study prove that wavelet transformation and the wavelet packet transformation may improve the effect in the remote sensing image fusion. Studied four kinds of rules of the low frequency information fusion which commonly used in image fusion based on the wavelet transformation and the wavelet packet transformation: Weighted Mean method, Local Energy method, Gradient method, Active Measure method, and propose the rule of image fusion based on Standard Deviation method. Summarizes some commonly used quota in estimating the quality of fusion images, Through analysis and comparison. Entropy, cross entropy, spectrum distorting index and edge index are employed to estimate the quality of fusion images. Studies in experimental result, obtaining the conclusions:1) The wavelet transformation and the wavelet packet transformation may improve effect of the traditional spectral enhancement image fusion based on the IHS transformation.2) Standard Deviation (SD) method and Local Energy method are the best two in balance with spectrum preserve and resolution enhancement for fusion of ETM+ remote sensing.3) The different fusion rule obtains different effect of fusion image, In view of concrete actual demand, Chooses the appropriate rule to carry on the fusion, Achieves the best effect of fusion image.