Land-use or land-cover classification of satellite images is one of the important tasks inremote sensing application and many researchers have tried to enhance classification accuracy. Previousstudies have shown that the classification technique based on wavelet transform is more effective thantraditional techniques based on original pixel values, especially in complicated imagery. Various basisfunctions such as Haar, daubechies, coiflets and symlets are mainly used in 2D image processing based onwavelet transform. Selecting adequate wavelet is very important because different results could be obtainedaccording to the type of basis function in classification. However, it is not easy to choose the basis functionwhich is effective to improve classification accuracy. In this study, we first computed the wavelet coefficientsof satellite image using ten different basis functions, and then classified images. After evaluating classificationresults, we tried to ascertain which basis function i