Study on tine LAI up-scaling based on mathematic transformation

How to apply some mathematic transformation in remote sensing scaling is investigated in this paper. The LAI (Leaf Area Index) up-scaling and Fourier and wavelet transformation are taken for example. Commonly, a larger spatial scale process is acquired by averaging the smaller scale remotely sensed process, but the high frequency components are eliminated by the averaging operation. Then Fourier transformation is a low-pass filter in essence, so the outline information of a remotely sensed image with high resolution can be gotten by Fourier transformation. However, some detailed information is also lost at the same time. Therefore, wavelet transformation is applied in Now, we can acquire the up-scaled image by combining the detailed information and the outline information. Test results shown that the overall evaluating index suggested in the paper is correct and reasonable. Transfer function related to scale correct factor is also introduced into this up-scaling method to improve the results. But it's a dependence factor. Further study on the scale correct factor and transformation parameters is doing.