J. S. Vitter, "Design and analysis of dynamic Huffman codes," Journal of the ACM, vol. 34, pp. 825--845, 1987. Home/Search Document Details and Download
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An Efficient Decoding Technique for Huffman Codes - Chowdhury, Kaykobad, King (2002) (Correct)
....to symbols the Huffman tree is Corresponding author. E mail addresses: shaikat2 yahoo.com, shaikat bdonline.com (R.A. Chowdhury) audwit bdonline.com (M. Kaykobad) king cse.cuhk.edu.hk (I. King) also sent. There is a single pass version of Huffman coding called dynamic Huffman coding [8]. In the latter case symbols are coded according to the frequencies of symbols sent so far, and the tree is updated by both sender and receiver using the same algorithm. In this paper we consider efficient decoding of the socalled static Huffman code. Hashemian [3] presented an algorithm to ....
J.S. Vitter, Design and analysis of dynamic Huffman codes, J. ACM 34 (4) (1987) 825--845.
On the Optimal Coding - Long, Jia (Correct)
....of data compression is given. Comparing with the Huffman coding, the optimal coding is a more flexible compression method used not only for statistical modeling but also for dictionary schemes. 1 Introduction The Huffman coding [6] has been widely used in data, image, and video compression [2 3, 9 14]. For instance, the Huffman coding is used to compress the result of a quantitative stage in JPEG [9] Huffman codes belongs into a family of codes with a variable length not a fixed length. That means that individual letter which makes a file encoded with bit sequences that have distinct length. ....
....a a . 1 = 2 1 c c k c is D N i . By the choice of c j (j=1, k) we easily obtain that D N =D N 1 D N 2 . D N (N 1) 1. Therefore, D N =D N 1 D N 2 . D N (N 1) 1 = 2 (D 1 1) 2 . Note that it is easy to verify that D 1 =1andD 2 =2. 4 Conclusion One disadvantage [14] of the Huffman coding is that it makes two passes over the data: one pass to collect frequency counts of the letters in the plaintext message, followed by the construction of a Huffman tree and transmission of the tree to the receiver; and a second pass to encode and transmit the letters ....
Vitter, J.S.: Design and Analysis of Dynamic Huffman Codes. Journal of the Association for Computing Machinery, 34(1987)4 825-845
The Burrows-Wheeler Transform: Theory and Practice - Manzini (1999) (Correct)
....and other small integers. For example, if s is an English text s usually contains more than 50 0 s. The actual compression is performed in the final step of the algorithm which exploits this skeweness of s. This is done using for example a simple zeroth order algorithm such as Huffman coding [36] or arithmetic coding [38] These algorithms are designed to achieve a compression ratio equal to the zeroth order entropy of the input string s which is defined by 5 H 0 (s) Gamma h X i=1 n i n log i n i n j ; 1) where n = jsj and n i is the number of occurrences of the symbol ff ....
J. Vitter. Design and analysis of dynamic Huffman codes. Journal of the ACM, 34(4):825--845, October 1987.
An Efficient Decoding Technique for Huffman Codes - Chowdhury, Kaykobad (Correct)
....the first pass, constructs a tree based upon which symbols receive codes. Then in the second pass symbols are coded and sent to the receiver. However, along with codes corresponding to symbols Huffman tree is also sent. There is a single pass version of Huffman coding called dynamic Huffman coding [8]. In the later case symbols are coded according to the frequencies of symbols so far sent, and the tree is updated by both sender and receiver using the same algorithm. In this paper we consider efficient decoding of the so called static Huffman code. Hashemian [3] presented an algorithm to speed ....
J. S. Vitter, Design and analysis of dynamic Huffman codes, Journal of the ACM, 34(4):825845, 1987.
On the Optimal Coding - Long, Jia (Correct)
....of data compression is given. Comparing with the Huffman coding, the optimal coding is a more flexible compression method used not only for statistical modeling but also for dictionary schemes. 1 Introduction The Huffman coding [6] has been widely used in data, image, and video compression [2 3, 9 14]. For instance, the Huffman coding is used to compress the result of a quantitative stage in JPEG [9] Huffman codes belongs into a family of codes with a variable length not a fixed length. That means that individual letter which makes a file encoded with bit sequences that have distinct length. ....
....2 1 c c k c is D N i . By the choice of c (j=1, k) we easily obtain that D N = D N 1 D N 2 . D N (N 1) 1. Therefore, D N = D N 1 D N 2 . D N (N 1) 1 = 2 N 2 (D 1 1) 2 N 1 . Note that it is easy to verify that D 1 = 1 and D 2 = 2. 4 Conclusion One disadvantage [14] of the Huffman coding is that it makes two passes over the data: one pass to collect frequency counts of the letters in the plaintext message, followed by the construction of a Huffman tree and transmission of the tree to the receiver; and a second pass to encode and transmit the letters ....
Vitter, J.S.: Design and Analysis of Dynamic Huffman Codes. Journal of the Association for Computing Machinery, 34(1987)4 825-845
On Synchronous Coding - Long, Jia, Li (2002) (Correct)
....optimal for a source alphabet if no other synchronous code has a smaller average code word length. Huffman published a method for constructing highly an efficient coding (or encoding) for finite source alphabets in 1952 [10] This method is known as the Huffman coding (or the Huffman s algorithm)[3 4,11,19 20,22,24,28 29]. 2. Optimal Synchronous Codes Motivated by existence of optimal synchronous codes, relationships among maximal prefix codes, optimal maximal prefix codes, Huffman codes, synchronous codes and optimal synchronous codes (if they exist) are first given. Recall from Chapter I in [2] that for a ....
....= 2 m 2 (Dm (m 1) 1) 2 m 2 (D 1 1) Note that it is easy to verify that D 1 = 1) 2 m 1 . According to Theorem 6, we have known that it is a NP complete problem to seek all possible synchronous codes that are used to encode the original message. 5. Conclusion One disadvantage [29] of the Huffman coding is that it makes two passes over the data: one pass to collect frequency counts of the letters in the plaintext message, followed by the construction of a Huffman tree and transmission of the tree to the receiver; and a second pass to encode and transmit the letters ....
[Article contains additional citation context not shown here]
J. S. Vitter, Design and Analysis of Dynamic Huffman Codes, Journal of the Association for Computing Machinery, 34(1987)4 825-845
Image Approximation by Self Affine Fractals - Dudbridge (1992) (4 citations) (Correct)
....algorithm replaces each word with a code whose length is inversely proportional to the frequency of that word, thereby optimizing the overall length of the sequence. Although the specification of the algorithm is simple and elegant, its efficient implementation remains an active area of research [1, 28]. Since the technique is lossless, it is often used as the final stage of lossy compression, in order to elicit further compression. We discuss the application of Huffman coding to fractal image approximation in chapter 7. The last few years have seen a concerted effort by the International ....
Vitter, J. S.: "Design and analysis of dynamic Huffman codes" Journal of the ACM 34:825-845 (1987) 60
Real-Time VLSI Compression for High-Speed Wireless Local Area .. - Jung, Burleson (1995) (1 citation) (Correct)
....can be either static or adaptive. For seamless integration of compression into an overall wireless LAN system, the compression need to be adaptive. Lossless data compression can also be either substitutional or statistical. In general a statistical compressor such as adaptive Huffman coding [19] or arithmetic coding [10] achieves a better compression ratio than a substitutional compressor such as Lempel Ziv [22] 23] However, the computing complexity and memory requirement for a statistical compressor are often much higher than a substitutional compressor. Substitutional compressors ....
Vitter, J., "Design and Analysis of Dynamic Huffman Codes," Journal of Association for Computing Machinery, pp. 825-845, October 1987.
Simple Bayesian Model for Bitmap Compression - Bookstein, Klein, Raita (2000) (2 citations) (Correct)
....If the performance is less than expected, then it indicates we should close the window and begin again. However, the decoder would not be able to follow the same decision procedure, because it does not know the next, incoming bits. This situation is inherent to many adaptive processes (see, e.g. Vitter (1987) and Welch (1984) and requires that we use a less efficient, delayed update strategy. The method we adopted is to simulate this strategy retrospectively: after each bit has been encoded, it is appended to the window W and we run a consistency check finalbayes.tex; 16 08 1999; 16:11; p.9 10 ....
Vitter J.S (1987) Design and analysis of dynamic Huffman codes. Journal of the ACM, 34:825--845.
An Analysis of the Burrows-Wheeler Transform - Manzini (1999) (7 citations) (Correct)
....close to the zeroth order entropy of the input string. More precisely, we assume that there exists a constant such that for any string s Order0(s) jsjH 0 (s) jsj: 11) It is well known that for static Huffman coding (11) holds with = 1. For the dynamic Huffman coding algorithm described in [22] (11) holds with = 2. Arithmetic coding routines exist in different flavors (see for example [10, 15, 25] each one with a different balance between storage requirements, compression, and speed. In [9] Howard and Vitter carry out a comprehensive analysis of arithmetic coding which tells us that a ....
J. Vitter. Design and analysis of dynamic Huffman codes. Journal of the ACM, 34(4):825-- 845, October 1987.
The WARM-UP Algorithm: A Lagrangean Construction of Length.. - Milidiu, Laber (1996) (1 citation) (Correct)
....(maxfw 1 ; xg; maxfw n ; xg) Let T x be a Huffman tree for the set w x . If h(T x ) L, then we are close to the conditions of theorem 1. That is true because x is the lowest weight of set w x , and leaves with equal weights are always arranged in consecutive levels in a Huffman tree [Vit87], in this case levels L and L Gamma 1. One question arises: how to select x The following theorem shows that if we increase the value of the parameter x, then the height of tree T x cannot increase. This monotone property suggests that we can determine an adequate value for x through a ....
....that h i h i 1 and h i h i 1 for i = 1; 2; Delta Delta Delta ; n Gamma 1 . Adding inequalities (3) and (4) we obtain that (t Gamma s) k X i=1 (h i Gamma h i ) k X i=k 1 (t Gamma w i ) h i Gamma h i ) 0 (5) Since we have k equal weights in the tree T t , it follows [Vit87] that h 1 h i h 1 Gamma 1 for i = 1; Delta Delta Delta ; k. The highest height in an optimal tree is associated to the lowest weight. Hence, it follows that h 1 = h(T Gamma s ) and h 1 = h(T t ) Now, let us suppose for absurd that h 1 h 1 . In this case we have that h i h i ....
Vitter J. S., Design and Analysis of Dynamic Huffman codes, Journal of ACM 34, 4, Oct, 825-845.
Document Image Compression and Analysis - Kia (1997) (3 citations) (Correct)
....on document image compression. 1.1 Image compression The initial breakthroughs in the compression of one dimensional signals [109] were easily extended to the image domain by concatenating image rows or columns into a single stream. Techniques such as Shannon Fano coding [95] and Huffman coding [26, 29, 55, 106, 118, 119] use redundancy reduction mechanisms which result in shorter codes for more frequently appearing samples. It is necessary to scan the data samples in order to determine their probabilities of occurrence and create an appropriate code. Adaptive variations of these techniques initially assume equal ....
J. Vitter. Design and analysis of dynamic Huffman codes. Journal of the Association for Computing Machinary, 34:825--845, 1987.
Improved Analysis of FGK Algorithm - Milidiu, Laber, Pessoa (1997) (Correct)
....loss due to a coding scheme different than Huffman coding, is defined by ffl = AC Gamma AH where AH is the average code length of a static Huffman encoding and AC is the average code length of an encoding based on the compression scheme C. When the scheme C is the FGK algorithm, Vitter[12] conjectured that ffl K for some real constant K. Here, we use an amortized analysis to prove this conjecture. We show that ffl 2. Furthermore, we show through an example that our bound is asymptotically tight. This result explain the good performance of FGK that many authors have observed ....
....de compress ao de um esquema de codificac ao e definida por ffl = AC Gamma AH onde AH e o comprimento m edio de uma codificac ao de Huffman e AC e o comprimmento m edio de uma codificac ao baseada em um esquema de compress ao C. Quando o esquema de compress ao e o algoritmo FGK, Vitter[12] conjeturou que ffl K para alguma constante real K. Neste trabalho, utilizamos uma t ecnica de an alise amortizada para provar esta conjectura. Al em disto, mostramos atrav es de um exemplo que nossa cota e justa. Este resultado explica o bom desempenho do FGK que alguns autores haviam ....
[Article contains additional citation context not shown here]
Vitter, J. S., Design and Analysis of Dynamic Huffman codes, Journal of ACM 34, 4(1987).
Is Huffman Coding Dead? - Bookstein, Klein (1993) (1 citation) (Correct)
.... Comparison of processing speed Note that encoding for arithmetic codes took more than twice as long as for Huffman codes, and decoding up to 10 times as long Since arithmetic codes can easily be used with an adaptive model, it is perhaps more fair to compare them with adaptive Huffman codes [19] [42], 30] as done in [43] Our results (columns headed adap H ) were however different from those reported in [43] yielding a decoding speed up to 6 times faster for adaptive Huffman codes than for arithmetic codes. There have been attempts to improve the speed of arithmetic codes, either ....
Vitter J.S., Design and analysis of dynamic Huffman codes, Journal ACM 34 (1987) 825--845.
Sub-linear Decoding of Huffman Codes Almost In-Place - Brodnik, Carlsson (1998) (1 citation) (Correct)
....encoding of a given text. Let us arrange N symbols with normalized frequencies i (0 i N) at leaves of a binary tree, where l i is the depth of the leaf. The binary tree with the minimal weighted external path length l = min N Gamma1 X i=0 i l i (1) is called the Huffman tree (cf. [5, 13]) A path from the root to the leaf in a binary tree can be encoded as a binary string where descending to the left (right) is represented with 0 (1) in the string. Using such a technique we can uniquely encode each symbol in the text. Moreover, these encodings are prefix free. The encoding ....
....brought down to N O(1) registers ( 9] There are numerous variations to the basic problem. In the basic version we have as an input the list of symbols with their frequencies. However, we do not always have a possibility to construct such a list. In this case we use dynamic Huffman coding (cf. [13, 14]) Even more generalized version of the problem is when we do not have the list of symbols either (cf. 7] Yet another version of the problem is to construct Huffman codes that must be shorter than some predefined constant (cf. 8] The solution presented in this paper can be applied to all ....
[Article contains additional citation context not shown here]
J.S. Vitter. Design and analysis of dynamic huffman codes. Journal of the ACM, 34(4):825--845, October 1987.
Fast and Efficient Lossless Image Compression - Howard, Vitter (1993) (19 citations) Self-citation (Vitter) (Correct)
....obtained with arithmetic coding without the time consuming arithmetic. It gives faster coding even than Huffman coding because of the especially simple prefix codes involved, and adaptive modeling is possible without the complicated data structure manipulations required in dynamic Huffman coding [2,3,9,15,16]. The main drawback to Golomb Rice coding is the limited class of distributions that can be modeled exactly, but even this is not a serious problem (unless one event s probability is close to 1) because the probabilities of the more probable events will be estimated fairly well. The idea of using ....
J. S. Vitter, "Design and Analysis of Dynamic Huffman Codes," Journal of the ACM 34 (Oct. 1987), 825--845.
Practical Implementations of Arithmetic Coding - Howard, Vitter (1992) (18 citations) Self-citation (Vitter) (Correct)
....especially when used with adaptive models [5] A single bit error in the encoded file causes the decoder s internal state to be in error, making the remainder of the decoded file wrong. In fact this is a drawback of all adaptive codes, including Ziv Lempel codes and adaptive Huffman codes [12,15,18,26,55,56]. In practice, the poor error resistance of adaptive coding is unimportant, since we can simply apply appropriate error correction coding to the encoded file. More complicated solutions appear in [5,20] in which errors are made easy to detect, and upon detection of an error, bits are changed ....
....the coding trees efficiently without using excessive space. The smallest average number of events coded per input symbol occurs when the tree is a Huffman tree, since such trees have minimum average weighted path length; however, maintaining such trees dynamically is complicated and slow [12,26,55,56]. In Section 3.3 we present a new data structure, the compressed tree, suitable for binary encoding of multi symbol alphabets. 2.3 Modeling for text compression 9 2.3 Modeling for text compression Arithmetic coding allows us to compress a file as well as possible for a given model of the ....
J. S. Vitter, "Design and Analysis of Dynamic Huffman Codes," Journal of the ACM 34 (Oct. 1987), 825--845.
Dynamic Shannon Coding - Travis Gagie Student (2004) (Correct)
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J. S. Vitter, "Design and analysis of dynamic Huffman codes," Journal of the ACM, vol. 34, pp. 825--845, 1987.
Compressing Extended Program Traces Using Value Predictors - Martin Burtscher Cornell (2003) (1 citation) (Correct)
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J. S. Vitter. "Design and Analysis of Dynamic Huffman Codes." Journal of the ACM, Vol. 34, No. 4, pp. 825-845. October 1987.
VPC3: A Fast and Effective Trace-Compression Algorithm - Martin Burtscher Computer (Correct)
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J. S. Vitter. "Design and Analysis of Dynamic Huffman Codes." Journal of the ACM, Vol. 34, No. 4, pp. 825-845. October 1987.
Cryptography in Data Compression - Wang (Correct)
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J.S. Vitter, Design and analysis of dynamic Huffman codes, in: J. ACM, 34, 4 (Oct.), 1987, 825-845.
Improving Information Retrieval System Security via an Optimal.. - Long (2002) (Correct)
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Vitter, J.S.: Design and Analysis of Dynamic Huffman Codes. Journal of the Association for Computing Machinery, 34(1987)4, 825-845
Low Complexity Sequential Lossless Coding for Piecewise.. - Shamir, Merhav (1999) (4 citations) (Correct)
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J. S. Vitter, "Design and analysis of dynamic Huffman codes," J. Ass. Comput. Mach., Vol. 34, pp. 825-845, Oct. 1987. 40
Hierarchical Enumerative Coding and Its Applications in Image.. - Oktem (Correct)
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J. S. Vitter, "Design and analysis of dynamic Huffman codes," Journal of the ACM, vol. 34, no. 4, pp. 825-845, October 1987.
Taking a Two-Dimensional view of character codes to facilitate.. - Es Si On (Correct)
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Vitter,J.S.,"Design and Analysis of Dynamic Huffman Codes" JACM, Vol. 34, No.4, Oct 1987, pp. 825-845
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