Several compression techniques need to be integrated for the achievement of effective low-bit-rate coding of moving images. Image entropy codes are used in conjunction with either predictive or transform coding methods. In this paper, we investigate the possible advantages of using arithmetric codes for image entropy coding. A theory of source modeling is established based on the concept of source parsing and conditioning trees. The key information-theoretic properties of conditioning trees are discussed along with algorithms for the construction of optimal and suboptimal trees. The theory and algorithms are then applied to evaluating the performance of entropy coding for the discrete cosine transform coefficients of digital images from the "Walter Cronkite" video sequence. The performance of arithmetic codes is compared to that of a traditional combination of run length and Huffman codes. The results indicate that binary arithmetic codes outperform run length codes by a factor of 55 percent for low-rate coding of the zero-valued coefficients. Hexadecimal arithmetic codes provide a coding rate improvement as high as 28 percent over truncated Huffman codes for the nonzero coefficients. The complexity of these arithmetic codes is suitable for practical implementation.

Motion compensation can be performed by either "forward-acting" or "backward-acting" motion detection. Forward algorithms require the transmission of motion vectors, whereas backward algorithms estimate the motion from two previously reconstructed frames at both the transmitter and receiver ends. For this reason, the backward systems are more attractive to low-rate videoconferencing applications. However, backward motion estimation may suffer some degradation due to varying speed of moving objects. In this paper we investigate the tradeoffs between the two schemes of motion compensation.

Progressive transmission and reconstruction of coded images allows an approximate image to be reconstructed based upon partially received information and adds details as additional information becomes available. This technique has various potential applications in the area of image communications, such as interactive picture retrieving, variable-rate video conferencing, and quick display for freeze-frame image transmission. We propose an optimal progressive transmission and reconstruction scheme for transformed images using bit-sliced bit assignment. Simulation results have shown that the bit-sliced progressive transmission scheme achieves a comparable performance at half of the bit rate required by the zigzag scanning approach.