Adaptive Compression Technique Research Articles

General‐purpose compression for efficient retrieval

Compression of databases not only reduces space requirements but can also reduce overall retrieval times. In text databases, compression of documents based on semistatic modeling with words has been shown to be both practical and fast. Similarly, for specific applications-such as databases of integers or scientific databases-specially designed semistatic compression schemes work well. We propose a scheme for general-purpose compression that can be applied to all types of data stored in large collections. We describe our approach-which we call RAY-in detail, and show experimentally the compression available, compression and decompression costs, and performance as a stream and random-access technique. We show that, in many cases, RAY achieves better compression than an efficient Huffman scheme and popular adaptive compression techniques, and that it can be used as an efficient general-purpose compression scheme.

A fast hardware data compression algorithm and some algorithmic extensions

This paper reports on work at IBM's Austin and Burlington laboratories concerning fast hardware implementations of general-purpose lossless data compression algorithms, particularly for use in enhancing the data capacity of computer storage devices or systems, and transmission data rates for networking or telecommunications channels. The distinctions between lossy and lossless compression and static and adaptive compression techniques are first reviewed. Then, two main classes of adaptive Lempel-Ziv algorithm, now known as LZ1 and LZ2, are introduced. An outline of early work comparing these two types of algorithm is presented, together with some fundamental distinctions which led to the choice and development of an IBM variant of the LZ1 algorithm, ALDC , and its implementation in hardware. The encoding format for ALDC is presented, together with details of IBM's current fast hardware CMOS compression engine designs, based on use of a content-addressable memory (CAM) array. Overall compression results are compared for ALDC and a number of other algorithms, using the CALGARY data compression benchmark file corpus. More recently, work using small hardware preprocessors to enhance the compression of ALDC on other types of data has shown promising results. Two such algorithmic extensions, BLDC and cLDC , are presented, with the results obtained on important data types for which significant improvement over ALDC alone is achieved.

Generalized wavelet decompositions in image compression: arbitrary subbands and parallel algorithms

New methods for lossy image compression based on gener- alized wavelet decompositions have been introduced recently. Unlike in the classical wavelet decomposition scheme, it is possible to use differ- ent scaling and wavelet functions at every scale by using nonstationary multiresolution analyses. This freedom in using different functions can be exploited for adaptive compression techniques. We extend this approach to arbitrary subbands (e.g., in a wavelet packet scheme), combine it with the best basis algorithm, and introduce efficient techniques for using these algorithms on parallel computers. © 1997 Society of Photo-Optical Instru- mentation Engineers. (S0091-3286(97)02805-5) Subject terms: image compression; wavelets; adaptive methods; parallel algo- rithms.

Knowledge-based approach to adaptive compression of telemetered data

An adaptive data compression technique based on a blackboard system is described. This approach provides highly efficient data reduction with the ability for the system to adapt to changes in the environment and the sensors, and also provides sensor fusion.

Adaptive discrete cosine transform coding algorithm for digital mammography

The need for storage, transmission, and archiving of medical images has led researchers to develop adaptive and efficient data compression techniques. Among medical images, x-ray radiographs of the breast are especially difficult to process because of their particularly low contrast and very fine structures. A block adaptive coding algorithm based on the discrete cosine transform to compress digitized mammograms is described. A homogeneous repartition of the degradation in the decoded images is obtained using a spatially adaptive threshold. This threshold depends on the coding error associated with each block of the image. The proposed method is tested on a limited number of pathological mammograms including opacities and microcalcifications. A comparative visual analysis is performed between the original and the decoded images. Finally, it is shown that data compression with rather high compression rates (11 to 26) is possible in the mammography field.

A practical adaptive image compression technique using visual criteria for still-picture transmission with electronic mail

An efficient image compression/decompression technique for complex scenes is presented. An image is first decorrelated by a full two-dimensional DCT (discrete cosine transform). The resulting coefficient map is weighted using properties of the human visual system and finally encoded with a novel multiresolution encoder. The result is converted into printable ASCII for transmission by electronic mail. >