We introduce a new image compression algorithm that allows progressive image reconstruction – both in resolution and in fidelity, with a fully embedded bit-stream. The algorithm is based on bit-plane entropy coding of reordered trans-form coefficients, similar to the progressive wavelet codec (PWC) previously introduced. Unlike PWC, however, our new progressive transform coder (PTC) does not use wavelets; it performs the space-frequency decomposition step via a new lapped biorthogonal transform (LBT). PTC achieves a rate vs. distortion performance that is comparable (within 2%) to that of the state-of-the-art SPIHT (set partitioning in hierarchical trees) codec. However, thanks to the use of the LBT, the space-frequency decomposition step in PTC reduces the number of multiplications per pixel by a factor of 2.7, and the number of ad-ditions by about 15%, when compared to the fastest possible implementation of the “9/7” wavelet transform via lifting. Furthermore, since most of the computation in the LBT is in fact performed by a DCT, our PTC codec can make full use of fast software and hardware modules for 1-D and 2-D DCTs.