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Computing problems that handle large amounts of data necessitate the use of lossless data compression for efficient storage and transmission. We present numerical results that showcase the advantages of a novel lossless universal data compression algorithm that uses parallel computational units to increase the throughput with minimal degradation in the compression quality. Our approach is to divide...
The present paper focuses on the compression system using Huffman compression algorithm for data compression. The rate of data decompression is more time consuming during the decoding of these compressed data. Various works have proposed for the enhancement of compressed data decoding. In this paper the realization and implementation of a High speed decoding Huffman coding system is proposed and the...
In this work we have implemented and discussed the performance evaluation of Least Significant Bit (LSB) and Least Significant Digit (LSD) on various formats of multimedia data. We have shown the performance variation on different formats for which these two techniques have been applied to hide the messages. Implementation of both the algorithms has been done to explore the security and distortion...
In recent years, cloud computing has emerged as a viable alternative for many computationally intensive applications. Offloading an application to the cloud has many advantages, but power consumption is still an important concern. Service providers should minimize power while maintaining customer's quality of service requirements. Dynamic Voltage and Frequency Scaling (DVFS) is an effective method...
It is proposed to introduce new methods of video data compression for more efficient use of wireless technology. Therefore, we propose the method of reconstructing digital static images based on the restoration of transforms. There is a technology of renovating values of vector of significant subbands of the nonuniform DCT spectrum on a known code and base; the vector of scaling components based on...
A seismic survey can produce a vast amount of data which is on the order of hundreds of terabytes. A high performance seismic data decompression algorithm can solve problems related not only to storage and transmission but also bandwidth. Decoding is one of the most expensive computational process in seismic data decompression due to the use of enthropy encoding algorithms as Huffman or arithmetic...
In this paper, the performance in terms of compression rates of fractal image compression using Fast Context Independent HV partitioning (FCI-HV) scheme and its variant fractal image compression using Fast Low Context Dependent HV partitioning (FLCD-HV) scheme are improved by applying loss-less data compression techniques on the fractal compressed image. By using loss-less data compression techniques...
This paper proposes a new two-dimensional antidictionary coding for a given rectangle. An antidictionary is the set of all the minimal forbidden rectangles for an input rectangle. The proposed encoder outputs a pair of an antidictionary and a unique polyomino which appears only once in an input rectangle as a codeword. The input rectangle can be decoded from the pair. Both the encoding and decoding...
This paper shows that a two-pass universal antidictionary coding method is asymptotically optimal for stationary ergodic sources with a finite alphabet. To prove the results, we propose a new compact tree representation of an antidictionary. We also extend the lossless compression algorithm proposed by Dubé and Beaudoin, called CSE, from the binary alphabet to the q-ary alphabet (q ≥ 2), which we...
The pseudo-distance technique (PDT) in lossless compression of color-mapped images has proved to be effective. We showed previously that by utilizing the PDT along with the Burrows-Wheeler transformation and an entropy coder, we obtained better compression gain than other well-known generic image compressors e.g. Portable Network Graphics (PNG). Most of these techniques have been designed as sequential...
The aim of this paper is to present a new static dictionary-based algorithm for text transformation to increase the data compression ratio when using standard compression tools. The basic idea of the new algorithm is to define a pattern for each word in a static dictionary by replacing all or most of the characters in the words of the dictionary by the most frequently used character in any text file...
A loss less dictionary based data compression technique has been proposed in this paper which is based on the optimality of LZW code. The compression process is started with empty dictionary and if the next symbol to be encoded is already in dictionary, length of symbol code is determined by the highest symbol code in the dictionary and encoded with the code in the dictionary. Otherwise, the symbol...
Large amount of data are generated in Global Navigation Satellite System (GNSS) simulation task, and the preservation and transmission of these data are a complex and time-consuming work. The data compression is an appropriate approach to solve the above problem. In this paper, the most mature and widely used lossless compression algorithm-the LZW algorithm is cited. For overcoming higher compression...
This paper presents an extrinsic data compression method for double-binary turbo codes. Frame and extrinsic data memory occupy more area in turbo decoder implementations with the frame size increasing. Besides, non-binary turbo codes have much more extrinsic memory usage than single-binary turbo codes. This proposed compression method utilizes an operation in radix-4 single-binary turbo decoder and...
Text compression techniques like bzip2 lack the possibility to delete the nth word or to insert text be-fore the nth word of compressed texts without prior decompression of the compressed texts. We present a text compression technique that supports fast insertion into and deletion from compressed texts without full decompression of the compressed text. Our approach combines Indexed Reversible Transformation...
In this paper, we develop a distributed compression technique that has low decoding and encoding computational complexity. The proposed scheme exploits both temporal and spatial correlations between nodes in distributed sensor networks. In case of events occurring, the values of both spatial and temporal might change and the compression technique needs to adjust its rate to the changes automatically...
In this paper, we refer to a new text transformation technique to move forward the existing lossless, reversible text makeover technique called Substitution coder. Substitution coder is a class of lossless text transformation algorithms which operates by searching for matches between the text to be compressed and a set of words contained in a dictionary, maintained by the coder. When the coder identifies...
In this paper, we present the performance evaluation of haptic compression methods for networked teleoperation systems or haptic interfaces in virtual environments. Haptic data, which include position, velocity, and force data exchanged through the communication channel, are considered by various compression methods based on down-sampling. We introduce the operational rate-distortion performance measure...
A novel loss less compression algorithm known as compression by sub string enumeration (CSE) is analyzed and modified. The CSE compression algorithm is a block-based, off-line method, as is the case with enumerative codes and the block-sorting compression scheme. First, we propose an encoding model that achieves asymptotic optimality for stationary ergodic sources. The codeword length attained by...
A method to compress aeroengine test data is discussed in this paper. Three characteristics of test data are analyzed firstly. They are limited value range, limited variation range and limited value precision. Based on the characteristics, four processes including reducing decimal digits, eliding sign bit, eliding repeated value and eliding redundant coding bits are utilized to compress the data....
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