Showing papers on "Canonical Huffman code published in 2002"

Canonical huffman encoded data decompression algorithm

Abstract: An apparatus and method for parallel decompression of compressed canonical Huffman encoded data.

Huffman decoding method and decoder, huffman decoding table, method of preparing the table, and storage media

Abstract: There are provided a Huffman decoding method and decoder which is capable of carrying out a decoding process at a high speed with a small memory capacity, and requires only a small-sized circuit. Input data encoded by a Huffman code is decoded. A Huffman decoding table is prepared which describes a binary tree corresponding to the Huffman code and having leaves each storing data. A binary tree-based search of the table is carried out based on the input data sequentially acquired by at least one bit to thereby decode the input data encoded by the Huffman code.

Joint product code optimization for scalable multimedia transmission over wireless channels

Abstract: State-of-the-art systems for the transmission of images over wireless channels generate an embedded bitstream and protect it with a product code where the row code is a concatenation of an outer cyclic redundancy check (CRC) code and an inner rate-compatible punctured convolutional (RCPC) code, and the column code is a Reed-Solomon (RS) code. In previous works, the product code was optimized by searching for the best RS protection for each RCPC code rate. We present a local search algorithm that jointly optimizes the RS and the RCPC codes. Experimental results show that our algorithm provides an approximately optimal solution, while its time complexity is much lower than that of the previous works.

Compression/decompression techniques based on tokens and Huffman coding

Abstract: Huffman coding ( 302 ) is first performed on uncompressed data ( 402 ) to obtain Huffman data ( 406 ). Additionally, the frequencies of one or more variable-length bit strings are also determined ( 408 ). At least one bit string is selected ( 304 ) when compression savings provided by the at least one bit string compares favorably with compression savings provided by the Huffman data. The Huffman data ( 406 ) is modified to account for the selection of the at least one bit string. Thereafter, compression is performed ( 306, 308 ) on the uncompressed data based on token replacements for the at least one bit string and, where necessary, on the modified Huffman data ( 420 ). In this manner, performance will be no worse than those techniques that employ Huffman coding. Using the present invention, greater compression efficiencies may be achieved without knowledge of the data being compressed while still preserving random accessibility of the data being compressed.

Ovsf code system and methods

Abstract: A code indexing method for orthogonal variable spreading factor codes (OVSF) introduces a single number mapped to each code. The new code number itself not only provides the code signature, but it is also used for the OVSF code generation. In addition, it provides easy and fast generation of the available code list without the help of look-up table. This capability improves the dynamic code assignment.

Generalized Shannon Code Minimizes the Maximal Redundancy

Abstract: Source coding, also known as data compression, is an area of information theory that deals with the design and performance evaluation of optimal codes for data compression. In 1952 Huffman constructed his optimal code that minimizes the average code length among all prefix codes for known sources. Actually, Huffman codes minimizes the average redundancy defined as the difference between the code length and the entropy of the source. Interestingly enough, no optimal code is known for other popular optimization criterion such as the maximal redundancy defined as the maximum of the pointwise redundancy over all source sequences. We first prove that a generalized Shannon code minimizes the maximal redundancy among all prefix codes, and present an efficient implementation of the optimal code. Then we compute precisely its redundancy for memoryless sources. Finally, we study universal codes for unknown source distributions. We adopt the minimax approach and search for the best code for the worst source. We establish that such redundancy is a sum of the likelihood estimator and the redundancy of the generalize code computed for the maximum likelihood distribution. This replaces Shtarkov's bound by an exact formula. We also compute precisely the maximal minimax redundancy for a class of memoryless sources. The main findings of this paper are established by techniques that belong to the toolkit of the "analytic analysis of algorithms" such as theory of distribution of sequences modulo 1 and Fourier series. These methods have already found applications in other problems of information theory, and they constitute the so called analytic information theory.

Signaling adaptive-quantization matrices in JPEG using end-of-block codes

Abstract: Previously-unused slots in a Huffman code table associated with a Joint Photographic Experts Group (JPEG) image file are associated with various quantization matrices (Q matrices) that are used to quantize data blocks of the JPEG image file Huffman codes associated with the various Q matrices permit the particular Q matrix used to quantize a given data block to be signaled by a decoder as an end-of-block (EOB) code The EOB codes and the Huffman code table are sent with the JPEG image file Upon decoding of the image file, a standard JPEG decoder reads each of the EOB codes as a standard JPEG EOB code and does not vary the Q matrix A modified decoder reads from each of the EOB codes which Q matrix was used to encode each particular data block of the image and uses that Q matrix to dequantize the data block

Code Generation Based on Trellis Diagrams

Abstract: In this chapter, the task of code generation is considered as a search problem for optimal weighted paths in trellis trees. These trees are made up of trellis diagrams containing information about the target machine’s instructions along with the required registers. An algorithm is discussed which integrates the highly interdependent tasks of scheduling, register allocation, and instruction selection. The trellis diagram concept is particularly useful when generating code for heterogeneous register set machines. It has been successfully applied to implement compilers for general purpose digital signal processors.

Decoding apparatus, decoding method, storage medium and program software

Abstract: A decoding apparatus has: M tables for storing, in correspondence with M types of variable-length code tables, minimum code words or maximum code words of classes of variable-length code words constructing a variable-length code table; a table selector which selects one table from the M tables; N comparators which compare input coded data with the minimum code words or maximum code words outputted from the table selected by the table selector; a switch circuit and a priority encoder which obtain a class number corresponding to an initial code word of the input coded data based on results of comparison by the N comparators; a code length converter which converts the class number into a code length; and an address generator which generates an address to access a memory holding decoded data from the class number and the code length outputted said code length converter. The data outputted from the memory based on the address becomes decoded data of the input coded data.

On the analysis of variable-to-variable length codes

Abstract: We simplify the formula for the redundancy of a large class of variable-to-variable length codes on discrete, memoryless sources and find new asymptotic upper bounds on the redundancy of the Tunstall-Huffman code and the Tunstall-Shannon-Fano code.

Searching in compressed dictionaries

Abstract: We introduce two new methods to represent a prefix omission method (POM) file so that direct search can be done in these compressed dictionaries. The processing time is typically twice as fast for the Fibonacci variant than for the Huffman based algorithm, and also compared to decoding a Huffman encoded POM file and searching on the uncompressed version. We see that in the case of small files, which is the important application since dictionaries are usually kept in small chunks, the Fibonacci variant is much faster than decoding and searching or than the POM-Huffman method. Even though the compression performance might be slightly inferior to the character version of Huffman (but still generally better than the bit version), this might well be a price worth paying for faster processing.

Decoding apparatus, method, and storage medium for inputting and decoding variable-length coded data

Abstract: A decoding apparatus has: M tables for storing, in correspondence with M types of variable-length code tables, minimum code words or maximum code words of classes of variable-length code words constructing a variable-length code table; a table selector which selects one table from the M tables; N comparators which compare input coded data with the minimum code words or maximum code words outputted from the table selected by the table selector; a switch circuit and a priority encoder which obtain a class number corresponding to an initial code word of the input coded data based on results of comparison by the N comparators; a code length converter which converts the class number into a code length; and an address generator which generates an address to access a memory holding decoded data from the class number and the code length outputted said code length converter. The data outputted from the memory based on the address becomes decoded data of the input coded data.

Condensed Huffman coding, a new efficient decoding technique

Abstract: A new technique is proposed for decoding Huffman codes. In this technique a Condensed Huffman Table (CHT) for decoding purposes replaces a typical Huffman table. It is shown that a CHT is much smaller in size and the decoding becomes significantly faster. In an example with a typical Huffman table containing 108 codewords, it is shown that a CHT with only 14 codewords is sufficient to perform the decoding.

Multi-table mapping for huffman code decoding

Abstract: Unique Huffman codes are generated with each being associated with a symbol. The unique codes are grouped according to a property of the unique codes such as length. The segments of a data stream to be decoded are compared with the grouped unique codes. Each segment has the same property as the grouped unique codes being compared with.

Approximating Huffman Codes in Parallel

Abstract: In this paper we present new results on the approximate parallel construction of Huffman codes. Our algorithm achieves linear work and logarithmic time, provided that the initial set of elements is sorted. This is the first parallel algorithm for that problem with the optimal time and work. Combining our approach with the best known parallel sorting algorithms we can construct an almost optimal Huffman tree with optimal time and work. This also leads to the first parallel algorithm that constructs exact Huffman codes with maximum codeword length H in time O(H) with n/logn processors, if the elements are sorted.

Method for image compression by modified Huffman coding

Abstract: The present invention provides a system that compresses and decompresses an image. The system includes a first codec a first stage codec for identifying runs of pixels of a defined value in a data stream of the image data beginning from the left and right margins of a line, such that information regarding the runs is assigned as a header and appended to the data stream. The compression device includes a second stage codec for scanning over remaining data in the data stream and compressing all but the header by utilizing a Huffman encoding scheme to reduce amount of data stored in the data stream, wherein the Huffman encoding scheme interleaves Huffman code values with unencrypted data while maintaining long word boundaries for the unencrypted data. The second codec also performs the operation of decompressing a compressed image.

Incremental calculation of minimum-redundancy length-restricted codes

Abstract: The prefix-free code construction problem is to take a message containing n unique symbols and produce a set of n codewords which can be used to create a reversible encoding of the message. The minimum-redundancy code construction problem adds the requirement that the code produced must minimise the cost of transmission (or storage) of the message. Adding another constraint, the minimum-redundancy length-restricted code construction problem is to create a minimum-redundancy code in which no codeword has a length greater than L bits. The solution to the minimum-redundancy code construction problem is due to Huffman (1952). The package-merge strategy of Larmore and Hirschberg (1990) is a two-stage mechanism for creating minimum-redundancy length-restricted codes. Their implementation, here called ORIGINAL-PM, requires O(nL) time and space. ORIGINAL-PM follows the underlying strategy closely and the following is a description of both the principle and that first implementation. Different implementation methods are discussed.

Optimal maximal and maximal prefix codes equivalent to Huffman codes

Abstract: Novel maximal coding and maximal prefix coding are introduced. We show that for finite source alphabets all Huffman codes are optimal maximal codes and optimal maximal prefix codes. Conversely, optimal maximal codes or optimal maximal prefix codes need not to be Huffman codes. For any maximal prefix code C, however, there exists some information source I such that C is exactly a Huffman code for I. And, for any maximal code C, there exists some information source I such that C is equivalent to a Huffman code for I. In other words, the class of Huffman codes coincides with the one of maximal prefix codes or maximal codes. Additionally, a case study of data compression is investigated. The optimal maximal coding and maximal prefix coding are used not only for statistical modeling but also for dictionary methods. Finally, it is proven that given an original file and a corresponding encoded file by the maximal prefix coding, the complexity of guessing the maximal prefix code is NP-complete.

Improving Information Retrieval System Security via an Optimal Maximal Coding Scheme

Abstract: Novel maximal coding compression techniques for the most important file-the text file of any full-text retrieval system are discussed in this paper. As a continuation of our previous work, we show that the optimal maximal coding schemes coincide with the optimal uniquely decodable coding schemes. An efficient algorithm generating an optimal maximal code (or an optimal uniquely decodable code) is also given. Similar to the Huffman codes, from the computational difficulty and the information-theoretic impossibility point of view, the problem of breaking an optimal maximal code is further investigated. Due to the Huffman code being a proper subclass of the optimal maximal code, which is good at applying to a large information retrieval system and consequently improving the system security.

Approximating Huffman Codes in Parallel

Abstract: In this paper we present new results on the approximate parallel construction of Huffman codes. Our algorithm achieves linear work and logarithmic time, provided that the initial set of elements is sorted. This is the first parallel algorithm for that problem with the optimal time and work.Combining our approach with the best known parallel sorting algorithms we can construct an almost optimal Huffman tree with optimal time and work. This also leads to the first parallel algorithm that constructs exact Huffman codes with maximum codeword length H in time O(H) and with n processors. This represents a useful improvement since most practical situations satisfy H = O(log n).

Method and apparatus for decoding compressed image data and capable of preventing error propagation

Abstract: In a method and apparatus for decoding an image data block having multiple data lines compressed into codeword streams, when one of multiple different code types and a line-end code, which are defined by a run-length encoding algorithm, is detected in an N-bit part of an M-bit segment of the codeword streams, the detected one of the code types and the line-end code is interpreted to generate a decompressed output. The N-bit part is further analyzed to find a succeeding one of the code types and the line-end code therein. When an error is detected in the N-bit part, a miss code is outputted to stop interpretation and further generation of the decompressed output. Analysis of the N-bit part is continued until the line-end code is detected. The line-end code is then interpreted so as to complete decompression of one of the data lines.

Using multiple Huffman code tables for optimal coding of DCT blocks

Abstract: Summary form only given. It is a well-known observation that when a DCT block is traversed in a zig-zag order, the AC coefficients generally decrease in size and the run-length of zero coefficients increase in number. Therefore, use of a single AC Huffman code table in the JPEG baseline algorithm leads to sub-optimal coding, and it is desirable to use multiple code tables, one for each DCT coefficient position, if necessary. It creates a problem, because a nonzero coefficient, X, and the run-length, Z, of zero coefficients that precede X, are coded as one element (Z,X), and therefore, the decoder may not know which table to use to decode the next X. To solve this problem, we made a minor modification to the JPEG Huffman coding algorithm. To evaluate reduction in the code size using our method, we compressed the luminancec component of ten well-known test images at default quality level and computed AC Huffman code size.

Improving Chinese Storing Text Retrieval Systems' Security via a Novel Maximal Prefix Coding

Abstract: We have seen that Huffman coding has been widely used in data, image, and video compression. In this paper novel maximal prefix coding is introduced. Relationship between the Huffman coding and the optimal maximal prefix coding are discussed. We show that all Huffman coding schemes are optimal maximal prefix coding schemes and that conversely the optimal maximal prefix coding schemes need not be the Huffman coding schemes. Moreover, it is proven that, for any maximal prefix code C, there exists an information source I = (∑ P) such that C is exactly a Huffman code for I. Therefore, it is essential to show that the class of Huffman codes is coincident with one of the maximal prefix codes. A case study of data compression is also given. Comparing the Huffman coding, the maximal prefix coding is used not only for statistical modeling but also for dictionary methods. It is also good at applying to a large information retrieval system and improving its security.