This paper studies the application of bit allocation using JPEG2000 for compressing multi-dimensional remote sensing data. Past experiments have shown that the Karhunen-Loeve transform (KLT) along with rate distortion optimal (RDO) bit allocation produces good compression performance. However, this model has the unavoidable disadvantage of paying a price in terms of implementation complexity. In this research we address this complexity problem by using the discrete wavelet transform (DWT) instead of the KLT as the decorrelator. Further, we have incorporated a mixed model (MM) to find the rate distortion curves instead of the prior method of using experimental rate distortion curves for RDO bit allocation. We compared our results to the traditional high bit rate quantizer bit allocation model based on the logarithm of variances among the bands. Our comparisons show that by using the MM-RDO bit rate allocation method result in lower mean squared error (MSE) compared to the traditional bit allocation scheme. Our approach also has an additional advantage of using DWT as a computationally efficient decorrelator when compared to the KLT