Weighted Burrows–Wheeler Compression

Software: Practice and Experience, 2002

The final coder in Burrows-Wheeler compression is usually either an adaptive Huffman coder (for speed) or a complex of arithmetic coders for better compression. This article describes the use of conventional pre-defined variable length codes or universal codes and shows that they too can give excellent compression. The paper also describes a "sticky Move-to-Front" modification which gives a useful improvement in compression for most files.

2014

Arithmetic coding is used in many compression techniques during the entropy encoding stage. Further compression is not possible without changing the data model and increasing redundancy in the data set. To increase the redundancy, we have applied index based byte-pair transformation (BPT-I) as a pre-processing to arithmetic coding. BPT-I transforms most frequent byte-pairs (2-byte integers). Here, most frequent byte-pairs are sorted in the order of their frequency and groups consisting of 256 byte-pairs are formed. Each byte-pair in a group is then encoded using two tokens: group number and the location in a group. Group number is denoted using variable length prefix codeword; whereas location within a group is denoted using 8-bit index. BPT-I is designed to be applied on any type of source; not necessarily text. More the number of groups considered during transformation, better is the compression. Experimental results have shown around 4.30 % additional reduction in compressed file...

Theoretical Computer Science, 2007

After a general description of the Burrows Wheeler Transform and a brief survey of recent work on processing its output, the paper examines the coding of the zero-runs from the MTF recoding stage, an aspect with little prior treatment. It is concluded that the original scheme proposed by Wheeler is extremely efficient and unlikely to be much improved. The paper then proposes some new interpretations and uses of the Burrows Wheeler transform, with new insights and approaches to lossless compression, perhaps including techniques from error correction.

Now days, computer technology mostly focusing on storage space and speed With the rapid growing of important data and increased number of applications, devising new approach for efficient compression and encryption methods are playing a vital role in performance. In this work, burrows wheeler transformation is introduced for pre processing of the input data and made several performance analysis experiments over different compression techniques for various types of text files and improved compression ratio has been found by applying burrows wheeler transform as pre-processing step.

International Journal of Web and Grid Services, 2008

In this paper, we present parallel algorithms for lossless data compression based on the Burrows-Wheeler Transform (BWT) block-sorting technique. We investigate the performance of using data parallelism and task parallelism for both multi-threaded and message-passing programming. The output produced by the parallel algorithms is fully compatible with their sequential counterparts. To balance the workload among processors we develop a task scheduling strategy. An extensive set of experiments is performed with a shared memory NUMA system using up to 120 processors and on a distributed memory cluster using up to 100 processors. Our experimental results show that significant speedup can be achieved with both data parallel and task parallel methodologies. These algorithms will greatly reduce the amount of time it takes to compress large amounts of data while the compressed data remains in a form that users without access to multiple processor systems can still use.

Abstract. ASCII characters have a different code representation where each character has a different numeric value between the characters to each other. The characters is usually used as a text message communication has the representation of a numeric code to each other or have a small difference. The value of the difference can be used as a substitution of the characters so it will generate a new message with a size that is a little more. This paper discusses the utilization value of the difference of characters ASCII in a message to a much simpler substitution by using a dynamic-sized window in order to obtain the difference from ASCII value contained on the window as the basis in determining the bit substitution on the file compression results.

2009

Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.

Fifth International Conference on Information Technology: New Generations (itng 2008), 2008

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.

2005

Compression is an economical and efficient way of data handling in not only communication, but also storage purposes. We aimed to implement a compression application based on frequent use of English letters, digraphs, trigraphs and tetragraphs without sacrificing memory and/or the other resources. Despite its conceptual simplicity, the approach achieves promising results. The system is tested for several data and the result was compared with LZW, Huffman Coding, and arithmetic coding. The system can be applied to either small or large files, and it can be seen that the result is still stable.

Modern Applied Science , 2018

Multimedia is highly competitive world, one of the properties that is reflected is speed of download and upload of multimedia elements: text, sound, pictures, animation. This paper presents CRUSH algorithm which is a lossless compression algorithm. CRUSH algorithm can be used to compress files. CRUSH method is fast and simple with time complexity O(n) where n is the number of elements being compressed.Furthermore, compressed file is independent from algorithm and unnecessary data structures. As the paper will show comparison with other compression algorithms like Shannon–Fano code, Huffman coding, Run Length Encoding, Arithmetic Coding, Lempel-Ziv-Welch (LZW), Run Length Encoding (RLE), Burrows-Wheeler Transform.Move-to-Front (MTF) Transform, Haar, wavelet tree, Delta Encoding, Rice &Golomb Coding, Tunstall coding, DEFLATE algorithm, Run-Length Golomb-Rice (RLGR).