The optimal design of quadtree-based vector quantizers is addressed. Until now, work in this area has focused on optimizing the quadtree structure for a given set of leaf quantizers with little attention spent on the design of the quantizers themselves. In cases where the leaf quantizers were considered, codebooks were optimized without regard to the ultimate quadtree segmentation. However, it is not sufficient to consider each problem independently, as separate optimization leads to an overall suboptimal solution. Rather, joint design of the quadtree structure and the leaf codebooks must be considered for overall optimality. The method we suggest is a "quadtree" constrained version of the entropy-constrained vector quantization design method. To this end, a centroid condition for the leaf codebooks is derived that represents a necessary optimality condition for variable-rate quadtree coding. This condition, when iterated with the optimal quadtree segmentation strategy of Sullivan and Baker (see IEEE Trans. on Image Processing, vol.3, p.327-331, May 1994) results in a monotonically descending rate-distortion cost function, and consequently, an (at least locally) optimal quadtree solution.

A discrete cosine transform image coding scheme based on adaptive block size is proposed and demonstrated. The scheme adaptively optimizes the block sizes according to some local activity indexes of the image scenes. The optimization is achieved by applying the technique from graph theory. Nine rectangular block sizes are used, corresponding to all combinations of 8, 16, and 32 pixels per side. This approach reduces interblock correlation between coefficients, and increases the energy compaction in the transform domain. Experimental results are presented and compared to results obtained by an identical coder using a fixed block size.>

An image coding method for low bit rates is proposed. It is based on alternate use of the discrete cosine transform (DCT) and the discrete sine transform (DST) on image blocks. This procedure achieves the removal of redundancies in the correlation between neighboring blocks as well as the preservation of continuity across the block boundaries. An outline of the mathematical justification of the method, assuming a certain first-order Gauss-Markov model, is given. The resulting coding method is then adapted to nonstationary real images by locally adapting the model parameters and improving the block classification technique. Simulation results are shown and compared with the performance of related previous methods, namely adaptive DCT and fast Karhunen-Loeve transform (FKLT).>

Methods are presented for enhancing one-dimensional variable-length differential pulse-code modulation (VLDPCM) images corrupted by transmission errors, are presented. The proposed methods take advantage of the VLDPCM code's high sensitivity to errors. Two methods are described. The first involves no increase of transmitted bit rate and consists of processing the corrupted image. The second method involves the transmission of additional information to enable an almost exact reconstruction of the original image. The amount of added redundancy can be reduced at the cost of performing more computations. In a simulation, the authors used less than 7% redundancy. Both methods achieve significant improvements which are demonstrated by the simulation results. The simulation results include original, corrupted, and enhanced images as well as the signal-to-noise ratio (SNR) versus bit-error rate (BER) curve. For BER 10/sup -3/, the SNR (signal-to-noise ratio) gains for the first and second methods are greater than 17 and 44 dB, respectively.>

A discrete cosine transform image-coding scheme based on adaptive block size is proposed and demonstrated. The scheme adaptively optimizes the block sizes according to some local activity indices of the image scenes. The optimization algorithm is achieved by applying a technique from graph theory. Nine rectangular block sizes are used, corresponding to all combinations of 8, 16, and 32, pixels per side. The approach reduces interblock correlation between coefficients and increases the energy compaction in the transform domain. Experimental results are presented and compared to results obtained by an identical coder using a fixed block size.>

A universal transformer for two-dimensional separable linear transforms in image coding is proposed. It is not restricted to fast transforms, and switching between transforms only requires writing the appropriate constants into an internal RAM. Look-up tables are used to reduce computational complexity. The linear transform properties are exploited to reduce the memory requirements by decomposing the input vector into smaller arrays and into bit planes. The input is pipelined into parallel data paths. An implementation example on a single gate array with existing technology achieves real-time transformation of 8 × 8 blocks, with area requirements of around 38K gates.