We present a low-complexity entropy coder originally designed to work in the JPEG2000 image compression standard framework. The algorithm is meant for embedded and non-embedded coding of wavelet coefficients inside a subband, and is called subband-block hierarchical partitioning (SBHP). It was extensively tested following the standard experiment procedures, and it was shown to yield a significant reduction in the complexity of entropy coding, with small loss in compression performance. Furthermore, it is able to seamlessly support all JPEG2000 features. We present a description of the algorithm, an analysis of its complexity, and a summary of the results obtained after its integration into the verification model (VM).

There are three basic segmentation schemes for compound image compression: object-based, layer-based, and block-based. This paper discusses the relative advantages of each scheme and architecture, and studies the use of fast classification techniques for a segmentation that can be used together with a chosen compression architecture. Particularly, we consider classification techniques working on approximate object boundaries, which reaches the localization and precision of the segmentation, but in exchange allows faster, one-pass segmentation, low memory requirements, and segmentation map that is better matched to existing compression methods. We show numerical results obtained on a printer application environment, where rigorous standards of visual quality have to be satisfied.

Most magnetic recording and many other digital communication channels exhibit statistical dependencies among errors. The design of error-control schemes for such channels .requires proper models and tools that can be used to evaluate error performance after decoding. In this paper a simplified partitioned model of a channel with memory suggested by B. D. Fritchman is considered. This model is used to derive expressions for block and bit error probability bounds for major block burst-error-correcting codes: interleaved, single burst-correcting, and nonbiuary codes. The model-based bounds are compared to the experimental ones using the data obtained for helical scan magnetic tape recorders. The comparison showed an agreement between experimental and analytical data within one order of magnitude, with the average difference being as small as 16 percent in some cases. A simple and effective implementation of a multiple burst-error-correcting scheme based on the majority-logic decoding of interleaved binary codes is suggested. The scheme requires about ten off-the-shelf IC's for both encoder and decoder with the interleaving degree up to 512.

Pulse frequency modulation (PFM) has been considered by several authors for transmitting wide-band signals. However, the noise performance of PFM has been analyzed only above the SNR threshold. In this correspondence the results on the noise performance of PFM available in the literature are summarized, and a more general expression describing noise performance of PFM, both above and below the SNR threshold, is derived. This expression can be used to evaluate the SNR threshold for channels with both signal-independent noise (e.g., metallic facilities) and signal-dependent noise (e.g., fiber optic facilities). In particular, it is shown that in systems with signal-independent white noise, the SNR threshold is approximately 20 dB.

An important feature of ARQ sequential decoding is that a very low undetected error probability can be achieved without increasing significantly the complexity of decoding. Several ARQ sequential decoding algorithms based on the stack algorithm are considered. Analysis is done for a memoryless channel with noiseless feedback, and the emphasis is on evaluating the undetected error probability and the maximum throughput attainable with each algorithm. A time-out algorithm is analyzed and the parameters optimizing the performance of this algorithm are found. A new algorithm called the slope control algorithm, capable of achieving a better throughput than the time-out algorithm, is proposed. The algorithm is analyzed using random coding arguments, and the parameters maximizing the throughput for various conditions are found. All theoretical results are verified by computer simulation for a binary symmetric channel.

ARQ methods of error control can considerably improve the reliablity of data transmission in such areas as satellite communications, computer networks, etc. A number of ARQ schemes using both block and convolutional codes have appeared in the literature. In this paper, the following problem is addressed. Given two different implementations of an ARQ scheme, one using a block code and the other using a convolutional code, such that the bit error probability of both implementations does not exceed some specific value, which implementation has the higher throughput and under what conditions will it be attained? The comparison is made for three basic retransmission schemes using both hybrid and pure ARQ: stop-and-wait, go-back-N, and selective repeat. Numerical estimates of the throughput were obtained using approximate theoretical expressions for BCH codes and simulation results for sequential decoding of rate 1/2 convolutional codes. Parameters optimizing the performance of both block and convolutional codes for different channel conditions and round trip delays were found and were used to obtain these numerical estimates. Comparison of the quantitative results indicates a trend toward preferring convolutional codes as delay and/or block length increases. A binary symmetric channel with noiseless feedback was assumed. Possible implications for the Gaussian channel are also discussed.