To solve the matching problem about the images got from different sensors, we present a new method based on intensity-based correlation. After analyzing the real match position and false match position from the correlation surface, we found a new method to search the real match position based on the feature of the peak on the correlation surface. Feature used in this method includes relative height of the peak, width of the peak and distinctness degree of the peak. Experiments show that this method is effective on the condition of proper sensed image size and resolution.
In this paper, the Fourier translation of 1-Dimension continuous signal is used to analysis the different frequency spectrum. The convolution of two signals can be expressed as the convolution of Fourier series of these two signals¡¯. After some translations and ignoring some secondary factors, the formula shows that in the correlation of two signals, the higher frequency of the images causes the narrow peak on the surface of the correlation. Comparing the original image and the correlation surface, we found the narrow peak on the correlation surface indicated the real matching position. All these shows that the stable unchanged feature usually contain in the higher frequency of the different images. To solve these matching problem of multi-spectral images, two methods are proposed, one is to do pretreatment (enhance the high frequency of the images to eliminate inconstant factors), the other is to search the narrow peak on the correlation surface. All these two methods are the same effect to locate the real matching position.
In the farther experiment, we found the matching problem not only between different spectral images, but also between the same spectral images but got at different time and different conditions had the same principle. The frequency analysis method can be extended to the problem of heterogeneous images matching.