Detecting Change Information Automatically by Method of Wavelet Coefficient Difference
Tow dimensional wavelet transform is widely used in various fields of image processing.It is utilized in landuse remote sensing dynamic monitoring to detect chang information automatically in the paper. By using PCA transform on the multi spectrum images of two different periods, the first three principal components were chosen to perform wavelet transform, and the two temporal wavelet coefficients of corresponding principal components were subtracted. It is detected that value difference of land using areas with no change was approximately zero, while the absolute value difference of the changing areas was great and with high energy, so the image performed wavelet counter transform can display land using changing areas with high brightness. Using image data to emulate and field validate the monitor result, the precision using the method mentioned here can meet the demand of practical application.
In this paper, we consider a network of N identical IEEE 802.11 DCF (Distributed Coordination Function) terminals with RTS/CTS mechanism, each of which is assumed to be saturated. For performance analysis, we propose a simple and efficient mathematical model to derive the statistical characteristics of the network such as the inter-transmission time of packets in the network and the service time (the inter-transmission time of successful packet transmissions) of the network. Numerical results and simulations are provided to validate the accuracy of our model and to study the performance of the IEEE 802.11 DCF network.