In this paper we discuss image matching by correlation in the subband domain with prospective applications. Theoretical proof is given to show that the correlation of two signals equals the weighted sum of the correlations of their decomposed subband signals. We propose an adaptive method to compute image correlation directly in the subband domain, which avoids decoding of the compressed data. Compared with pixel-domain correlation, this method reduces computation by more than ten times with satisfactory accuracy. We also compare the effects of template size, number of iterations of subband decomposition, and filter type on the speed and accuracy. Complexity estimations and test results are given. In addition, several techniques that involve image correlation are investigated for application in image matching.