Showing papers on "Modified Huffman coding published in 1992"
TL;DR: The authors describe an adaptive buffer instrumented version of 2-D ECSBC, for use with fixed-rate channels which completely eliminates buffer overflow/underflow problems and provides relative performance evaluations.
Abstract: The authors describe a design approach, called 2-D entropy-constrained subband coding (ECSBC), based upon recently developed 2-D entropy-constrained vector quantization (ECVQ) schemes. The output indexes of the embedded quantizers are further compressed by use of noiseless entropy coding schemes, such as Huffman or arithmetic codes, resulting in variable-rate outputs. Depending upon the specific configurations of the ECVQ and the ECPVQ over the subbands, many different types of SBC schemes can be derived within the generic 2-D ECSBC framework. Among these, the authors concentrate on three representative types of 2-D ECSBC schemes and provide relative performance evaluations. They also describe an adaptive buffer instrumented version of 2-D ECSBC, called 2-D ECSBC/AEC, for use with fixed-rate channels which completely eliminates buffer overflow/underflow problems. This adaptive scheme achieves performance quite close to the corresponding ideal 2-D ECSBC system. >
83 citations
24 Mar 1992
TL;DR: An algorithm based on the hierarchical multi-level progressive (MLP) method is presented, used either with Huffman coding or with a new variant of arithmetic coding called quasi-arithmetic coding.
Abstract: The authors show that high-resolution images can be encoded and decoded efficiently in parallel. They present an algorithm based on the hierarchical multi-level progressive (MLP) method, used either with Huffman coding or with a new variant of arithmetic coding called quasi-arithmetic coding. The coding step can be parallelized, even though the codes for different pixels are of different lengths; parallelization of the prediction and error modeling components is straightforward. >
58 citations
Patent•
26 Jun 1992TL;DR: In this paper, a method and a structure are provided for decoding Huffman codes using a random access memory having a size less than twice the total number of codewords decodable.
Abstract: A method and a structure are provided for decoding Huffman codes using a random access memory having a size less than twice the total number of codewords decodable. Under this method, the number of leading 1's in a Huffman codeword and the bits of the Huftman code word other than the leading 1's ("remainder") are combined to form an address into the random access memory. Using the fact that, for a given number of leading 1's in a Huffman code, the possible remainder of the Huffman code is no longer than a predetermined number of bits, the size of the random access memory necessary for decoding such Huffman codes can be made optimally small.
34 citations
Journal Article•
12 citations
TL;DR: Variable-to-fixed-length coding implementations, according to the Tunstall algorithm, are shown to be significantly less complex than fixed- to-variable- length coding schemes such as the Huffman scheme.
Abstract: Variable-to-fixed-length coding implementations, according to the Tunstall algorithm, are shown to be significantly less complex than fixed-to-variable-length coding schemes such as the Huffman scheme. A modified version of Tunstall coding is presented, with improved compression ratio.
11 citations
28 May 1992
TL;DR: By applying a variant Huffman coding method, it is possible to represent the Huffman tree of suffixes in the form of another dictionary, to which the method can be iteratively applied.
Abstract: Front-coding is a technique used to reduce the redundancy in a representation of a dictionary, taking advantage of common prefixes. However, redundancy still exists in the front-coded representation; suffixes and infixes of words are not coded. The authors method attempts to remedy this deficiency by iteratively applying front-coding techniques to the suffixes. By applying a variant Huffman coding method, it is possible to represent the Huffman tree of suffixes in the form of another dictionary, to which the method can be iteratively applied. On large natural-language dictionaries the authors have achieved compression ratios as favourable as 11%. >
6 citations
16 Nov 1992
TL;DR: The restricted variable length coding method using multiples of 4-bit code values is simple in concept and easy to implement and the compression results are comparable with what the LZW method achieves, and the compressed/decompression process it slightly faster.
Abstract: This paper reports on the results of the study of a two-pass reversible data compression scheme. The restricted variable length coding method using multiples of 4-bit code values is simple in concept and easy to implement. The compression results and the compression/decompression times regarding four large Chinese text files are superior to those using character-based two-pass Huffman coding and adaptive Huffman coding methods. The compression results are comparable with what the LZW method achieves, and the compression/decompression process it slightly faster. >
5 citations
Proceedings Article•
1 Jan 1992
TL;DR: This document describes the design and construction of the LTS-ARTICLE-1992-001 model and some of the features that were developed during the development of this model.
Abstract: Keywords: LTS1 ; LTS3 Reference LTS-ARTICLE-1992-001 Record created on 2006-06-14, modified on 2016-08-08
4 citations
1 Jan 1992
TL;DR: This chapter discusses the Huffman coding and arithmetic coding methods of data compression and presents an implementation of the latter algorithm, which allows a tradeoff among memory consumption and compression ratio.
Abstract: This chapter discusses the Huffman coding and arithmetic coding methods of data compression and presents an implementation of the latter algorithm. The arithmetic coding algorithm allows a tradeoff among memory consumption and compression ratio. It focuses on minimum memory consumption, on the assumption that the result is used as embedded code within a larger program. One of the most powerful methods of improving the efficiency of a given algorithm is the recoding of critical areas of the program that is applied in assembly language. While the exact details of this enhancement are specific to machines based on the 80 × 86 architecture, the principles that are used to focus effort are generally applicable. Huffman coding is widely recognized as the most efficient method of encoding characters for data compression. This algorithm is a way of encoding different characters in different numbers of bits, with the most common characters encoded in the fewest bits. Using Huffman coding, there is no way to assign theoretically optimal codes to characters with such a frequency distribution. As the shortest possible Huffman code is one bit, the best one can do is to assign a one-bit code to each character, although this does not reflect the difference in their frequencies. In fact, Huffman coding can never provide any compression with a two character alphabet.
2 citations