The 2-Dimensional Wavelet Transform has been proven to be a highly effective tool for image analysis and used in JPEG2000 standard. There are many publications which demonstrate that using wavelet transform in time and space, combined with a multiresolution approach, leads to an efficient and effective method of compression. In particular, the four and six coefficient Daubechies filters have excellent spatial and spectral locality, properties which make them useful in image compression. In this paper, we propose a multiplication-free and parallel VLSI architecture for Daubechies wavelets where the computations are free from round-off errors until the final reconstruction step. In our algorithm, error-free calculations are achieved by the use of Algebraic Integer encoding of the wavelet coefficients. Compared to other DWT algorithms such as: embedded zero-tree, recursive or semi-recursive and conventional fixed-point binary architecture, our technique has lower hardware cost, lower computational power and optimized data-bus utilization.