Showing papers on "Canonical Huffman code published in 2008"

Method for Compressed Data with Reduced Dictionary Sizes by Coding Value Prefixes

Abstract: The speed of dictionary based decompression is limited by the cost of accessing random values in the dictionary. If the size of the dictionary can be limited so it fits into cache, decompression is made to be CPU bound rather than memory bound. To achieve this, a value prefix coding scheme is presented, wherein value prefixes are stored in the dictionary to get good compression from small dictionaries. Also presented is an algorithm that determines the optimal entries for a value prefix dictionary. Once the dictionary fits in cache, decompression speed is often limited by the cost of mispredicted branches during Huffman code processing. A novel way is presented to quantize Huffman code lengths to allow code processing to be performed with few instructions, no branches, and very little extra memory. Also presented is an algorithm for code length quantization that produces the optimal assignment of Huffman codes and show that the adverse effect of quantization on the compression ratio is quite small.

Test Data Compression Based on Variable-to-Variable Huffman Encoding With Codeword Reusability

Abstract: A new statistical test data compression method that is suitable for IP cores of an unknown structure with multiple scan chains is proposed in this paper. Huffman, which is a well-known fixed-to-variable code, is used in this paper as a variable-to-variable code. The precomputed test set of a core is partitioned into variable-length blocks, which are, then, compressed by an efficient Huffman-based encoding procedure with a limited number of codewords. To increase the compression ratio, the same codeword can be reused for encoding compatible blocks of different sizes. Further compression improvements can be achieved by using two very simple test set transformations. A simple and low-overhead decompression architecture is also proposed.

Bit-stream huffman coding for data compression

Abstract: Bit-stream Huffman coding may be used for data compression to quickly and efficiently compress relatively small and large datasets. A symbol used in data compression may not be a byte or 8 bits. Rather it has any number of bits. For a certain dataset, a symbol has a dynamic number of bits according to the data size. A symbol may have less than 8 bits for a small dataset, or more than 8 bits for a large dataset. For rapid processing, a large dataset may be broken into smaller datasets that are fast encoded in parallel. Accordingly, the Huffman encoding inputs from a bit-stream instead of a conventional byte-stream and outputs a bit-stream. In particular, bit-stream Static and Adaptive Huffman codings are presented with extended algorithms. Hardware implementation with parallel Huffman encoders and decoders is also illustrated for fast network data compression.

Adaptive vector Huffman coding and decoding based on a sum of values of audio data symbols

Abstract: An audio encoder performs entropy encoding of audio data For example, an audio encoder determines a Huffman code from a Huffman code table to use for encoding a vector of audio data symbols, where the determining is based on a sum of values of the audio data symbols An audio decoder performs corresponding entropy decoding

Sequential adaptive compressed sampling via Huffman codes

Abstract: There are two main approaches in compressed sensing: the geometric approach and the combinatorial approach. In this paper we introduce an information theoretic approach and use results from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a sparse signal. Unlike other approaches, our approach is adaptive in the sense that each sampling vector depends on the previous sample. The number of measurements we need for a k-sparse vector in n-dimensional space is no more than O(k log n) and the reconstruction is O(k).

The evolution and trend of chain code scheme

Abstract: Chain code is an image method representation based on region boundaries. The chain code of region is determined by specifying a starting pixel and the sequence of unit vectors obtained from going either left, right, up, or down in moving from pixel to pixel along the boundary. Chain code is widely used nowadays because it preserves information and allows considerable data reduction. The first approach for representing digital curves using chain code was introduced by Freeman in 1961, and it is known as Freeman Chain Code (FCC). This code follows the contour in counter clockwise manner and keeps track of the directions as we go from one contour pixel to the next. The codes involve 4– connected and 8– connected paths. Since it was introduced by Freeman, the development of chain code and its application increases rapidly. This paper explains some chain code concepts and their applications that are be the background of the development of vertex chain code cells algorithm. This algorithm is able to visualize and to transcribe a binary image into vertex chain code easily. Some examples are also presented.

A Test Data Compression Method for System-on-a-Chip

Abstract: This paper presents a novel and efficient code, named MFDR (modified frequency-directed run-length) , for test data compression. The proposed code is a class of variable-to-variable-length prefix code. Both theoretical analysis and experimental results indicate that when the probability of 0s in the test set is greater than 0.8565, it can acquire better compression efficiency than FDR code, and compared to hybrid run-length code, the point is 0.8794.

Guaranteed Synchronization of Huffman Codes

Abstract: In a text encoded with a Huffman code a bit error can propagate arbitrarily long. This paper introduces a method for limiting such error propagation to not more than L bits, L being a parameter of the algorithm. The method utilizes the inherent tendency of the codes to synchronize spontaneously and does not introduce any redundancy if such a synchronization takes place.

Fourier code: A novel orthogonal code for OCDM systems

Abstract: The correlation property of the complex-valued OCDM code, the Fourier code, has been investigated. It provides easier implementation as well as lower aperiodic cross-correlation than the well-known binary Hadamard code.

Camera based code reading

Abstract: Techniques for providing camera based code reading are disclosed. In some aspects, a camera-readable code is generated which may be read by a code reading device. The code reading device may capture an image of the code, process the image, and decode the code. The code includes symbols arranged to form a pattern. According to one or more embodiments, an image with the code is cropped to remove extraneous information. The code image is manipulated by exact binary segmentation to remove background information from the code. The code is oriented to a grid using an interval value defined between the symbols. The symbols are decoded by comparing unique aspects of the symbols using a statistical analysis. The decoded symbols may be converted to a message for a user or be used for other purposes.

Memory Efficient Hierarchical Lookup Tables for Mass Arbitrary-Side Growing Huffman Trees Decoding

Abstract: This paper addresses the optimization problem of minimizing the number of memory access subject to a rate constraint for any Huffman decoding of various standard codecs. We propose a Lagrangian multiplier based penalty-resource metric to be the targeting cost function. To the best of our knowledge, there is few related discussion, in the literature, on providing a criterion to judge the approaches of entropy decoding under resource constraint. The existing approaches which dealt with the decoding of the single-side growing Huffman tree may not be memory-efficient for arbitrary-side growing Huffman trees adopted in current codecs. By grouping the common prefix part of a Huffman tree, in stead of the commonly used single-side growing Huffman tree, we provide a memory efficient hierarchical lookup table to speed up the Huffman decoding. Simulation results show that the proposed hierarchical table outperforms previous methods. A Viterbi-like algorithm is also proposed to efficiently find the optimal hierarchical table. More importantly, the Viterbi-like algorithm obtains the same results as that of the brute-force search algorithm.

A Fast and Memory Efficient Huffman Decoding Method for the MPEG-4 AAC Standard

Abstract: Huffman coding is an efficient coding technique that is largely used in applications that need a lossless data compression. We present in this paper a novel method for Huffman decoding that increases the performance and keeps the memory consumption low. The main idea is to add information about the number of bits necessary to search for the next possible symbol in the Huffman tree. The proposed method has been used in the implementation of an MPEG-4 AAC decoder, and has proven to be extremely fast to decode short symbols that are the ones with higher probability to occur in a bitstream.

A fast parallel huffman decoder for fpga implementation

Abstract: The paper presents a novel algorithm and architecture for implementing a Huffman decoder. It starts with an overview of the basics, from the entropy coding and the way the Huffman coding is obtained, to the way a Huffman coder handles data and image components within the Jpeg standard. Then it briefly discusses the decoding procedures proposed by the ISO/IEC 10918- 1(1993E) standard; due to their sequential nature, a decoder that simply implements these procedures requires several execution cycles to output one set of decoded data. A new decoding algorithm is then introduced, based on a parallel architecture that allows it to output a set of decoded data per each clock cycle. This approach was validated through actual implementation on an of-the- shelf FPGA; this not only demonstrates the proposed algorithm and architecture but also proves that it can operate at very high frequencies, up to 100MHz. A limitation of this implementation is the relatively large amount of hardware resources it requires.

Canonical Huffman code based full-text index

Abstract: Full-text indices are data structures that can be used to find any substring of a given string. Many full-text indices require space larger than the original string. In this paper, we introduce the canonical Huffman code to the wavelet tree of a string T [1… n ]. Compared with Huffman code based wavelet tree, the memory space used to represent the shape of wavelet tree is not needed. In case of large alphabet, this part of memory is not negligible. The operations of wavelet tree are also simpler and more efficient due to the canonical Huffman code. Based on the resulting structure, the multi-key rank and select functions can be performed using at most nH 0 + ∣ Σ ∣(lg lg n + lg n − lg ∣ Σ ∣)+ O ( nH 0 ) bits and in O ( H 0 ) time for average cases, where H 0 is the zeroth order empirical entropy of T . In the end, we present an efficient construction algorithm for this index, which is on-line and linear.

A Study and Implementation of the Huffman Algorithm Based on Condensed Huffman Table

Abstract: Huffman codes are being widely used as a very efficient technique for compressing data. To achieve high compressing ratio, some properties of encoding and decoding for canonical Huffman table are discussed. A study and implementation of the Huffman algorithm based on condensed Huffman table is studied. New condensed Huffman table could reduce the cost of the Huffman coding table. Compared with traditional Huffman coding table and other improved tables, the best advantages of new condensed Huffman table is that the space requirement is reduced significantly.

A low power high performance design for JPEG Huffman decoder

Abstract: JPEG image codec is one of the most commonly used standards for communication and storage applications. In this paper, we propose a simple and successful design for a JPEG alternating current Huffman decoder with low power and high performance considerations. Based on the parallel Huffman decoder structure, we utilize the bipartition architecture on the lookup table to reduce power consumption without sacrificing decoding performance. Gate level power simulation results show a maximum of 25% power reduction can be obtained when compared with the conventional JPEG parallel Huffman decoder.

A Low-Latency Multi-layer Prefix Grouping Technique for Parallel Huffman Decoding of Multimedia Standards

Abstract: Huffman coding is a popular and important lossless compression scheme for various multimedia applications. This paper presents a low-latency parallel Huffman decoding technique with efficient memory usage for multimedia standards. First, the multi-layer prefix grouping technique is proposed for sub-group partition. It exploits the prefix characteristic in Huffman codewords to solve the problem of table size explosion. Second, a two-level table lookup approach is introduced which can promptly branch to the correct sub-group by level-1 table lookup and decode the symbols by level-2 table lookup. Third, two optimization approaches are developed; one is to reduce the branch cycles and the other is parallel processing between two-level table lookup and direct table lookup approaches to fully utilize the advantage of VLIW parallel processing. An AAC Huffman decoding example is realized on the Parallel Architecture Core DSP (PAC DSP) processor. The simulation results show that the proposed method can further improve about 89% of decoding cycles and 33% of table size comparing to the linear search method.

Assigning Codes to and Repairing Huffman Trees

Abstract: A method for assigning codes to Huffman trees and repairing invalid Huffman trees is disclosed using a calculated delta and moving nodes within the Huffman tree by adjusting their encode register entries.

Huffman Coding with Non-sorted Frequencies

Abstract: A standard way of implementing Huffman's optimal code construction algorithm is by using a sorted sequence of frequencies. Using only partial order may speed up the code construction, which is important in some applications, at the cost of possibly increasing the size of the encoded file.

Observations on Compressing Text Files of Varying Length

Abstract: The paper compares different data compression algorithms of text files: LZW, Huffman, fixed-length code (FLC), and Huffman after using fixed-length code (HFLC). We compare these algorithms on different text files of different sizes in terms of compression scales of: size, ratio, time (speed), and entropy. Our evaluation reveals that initially for smaller size files the simplest algorithm namely LZW performs worst for first two scales than the more complex Huffman algorithm but as the size of the text increases interestingly the position is reversed. Moreover for the scales time and entropy LZW performs better than Huffmans but for larger files once again the position is reversed.

Code Transformation Algorithms for Two Breadth-First Linear Quadtrees

Abstract: In this paper, the code transformation algorithms between the fixed binary linear quadtree scheme (FBLQ)and the constant bit-length linear quadtree scheme(CBLQ) are proposed. There exists no code transformation algorithm between FBLQ and CBLQ. To solve this problem that when one receives a FBLQ or CBLQ code and does not have the corresponding decoding program, with our new code transformation algorithms at hand, she/he can transform the received code into CBLQ or FBLQ code that she/he can handle.The code transformation algorithms can also be used to reduce the load an image lays on the system by transforming it from a higher complexity code to a lower one.

New Data Compression Algorithm Based on Huffman Coding

Abstract: A new way for file compression is discussed,It is taken as a binary stream composed either by 0 or 1,and defined several bits as a word,so in a way the file is a stream of words.The frequency of these different words is surved,and then compress them using the Huffman algorithm.finally the compression rate of different words in multiple files is studyied,and given comparative results under these circumstance.

Decoder and method for decoding a message using an arbitrary-side growing Huffman tree

Abstract: A decoder for decoding a message using an arbitrary-side growing (ASG) Huffman tree including a plurality of codewords and symbols includes a database, a processing module, and a bit pattern matching module. The database stores a plurality of parameters corresponding to the ASG Huffman tree divided into several sub-trees according to a Hashemian cut operation and a bits-pattern-Xor (BPX) operation. The plurality of parameters include a bit pattern of a sub-tree of the ASG Huffman tree divided according to the BPX operation and a code length of the bit pattern. The processing module receives a bit stream corresponding to the ASG Huffman tree from an encoder. The bit pattern matching module selects bits from the bit stream according to the code length of the bit pattern and decodes the selected bits into a symbol in the ASG Huffman tree by comparing the selected bits with the bit pattern.

Context-Based Entropy Encoding Method for Connectivity Compression of Meshes

Abstract: A general efficient algorithm for entropy encoding of the connectivity information of meshes is presented in this paper. In comparison to the previous encoding methods, which use only Huffman or arithmetic coding method to encode operator series, this coding method can efficiently compress connectivity information by first calculating Huffman code for every symbol in connectivity series, followed by encoding the Huffman code through using a context-based arithmetic coding method. Experimental results indicate that this method can be applied to almost all the connectivity compression algorithms for meshes. The compression result by using this entropy encoding method is generally higher than the entropy of the series—the best compression result that most

An efficient and hardware-implementation-friendly algorithm for adaptive Huffman coding

Abstract: Adaptive Huffman coding is preferred in communication systems due to its capability in real-time processingAn efficient algorithm for adaptive Huffman coding is presentedThe new algorithm utilizes the similarity between the construction processes of the Huffman tree before and after symbol′s arrival,and updates much less nodes than Algorithm V to accomplish the code processingConsequently,the complexity is significantly reduced,the space and time consuming is saved,and hence hardware implementation is greatly simplified

Switching code data compression technique using an Adaptive Huffman coding

Abstract: A number of data compression techniques have been introduced to reduce the text/data storage and transmission costs. The Proposed compression method in this paper is based on Switching code data compression technique using adaptive Huffman coding. The encoding process of the system encodes frequently occurring characters with shorter bit code and infrequently occurring appearing characters with longer bit codes, same code can be use for three symbols for alphabet, number and special character. The decoding process expands the encoded data back to the original data and works very much like the encoder process. Proposed method is more effective than Adaptive Huffman coding because it reduce the codeword length of the characters and can be use same codeword for three different groups character. Their size of the symbol-codeword table is also reduces which transmitted with the compressed data. This process enhancing compression efficiency up to 12% more then Adaptive Huffman Coding which provide compression ratio up to 52.51%(+12%). The developed system is very effective for compressing text file, which hold numbers and special symbols approximately equi-probable to alphabets like Math's Books/database files in a real time environment.

Penggunaan Algoritma Huffman Untuk Kompres Teks

Abstract: Method compression of text by using algorithm Huffman gives storage thrift of data. This method is algorithm that is most famous to compress of text. This algorithm applies system encoding with bit network, where character which the frequency is often is decoded with short bit network and character which the frequency seldom be decoded with long bit network. There is three steps in using algorithm Huffman that is first phase of forming of tree Huffman where at this phase by using this Huffman tree minimization of scanning path length will by the way of putting down information often emerges close to root and information which seldom emerge far from root, second phase is encoding that is way is compiling string binary read from root up to tree leaf Huffman, and third phase that is decoding returns from code which has been formed. Keywords : Huffman’s Algorithm, Huffman Tree, Encoding, Decoding

Better Huffman coding via genetic algorithm

Abstract: We present an approach to compress arbitrary files using a Huffman-like prefix-free code generated through the use of a genetic algorithm, thus requiring no prior knowledge of substring frequencies in the original file. This approach also enables multiple-character substrings to be encoded. We demonstrate, through testing on various different formats of real-world data, that in some domains, there is some significant advantage to using this genetic approach over the traditional Huffman algorithm and other existing compression methods.