scholarly journals Abstract Alphabet Sliding-Block Entropy Compression Coding with a Fidelity Criterion

1980 ◽  
Vol 8 (6) ◽  
pp. 1085-1092 ◽  
Author(s):  
James G. Dunham
Keyword(s):  
Block Entropy ◽  
Entropy Compression ◽  
Compression Coding

An Adaptive JPEG Steganographic Scheme Based on the Block Entropy of DCT Coefficients

2012 ◽  
Vol 4 (2) ◽  
pp. 13-27
Author(s):  
Chang Wang ◽  
Jiangqun Ni ◽  
Chuntao Wang ◽  
Ruiyu Zhang
Keyword(s):  
Rounding Errors ◽  
Trellis Coding ◽  
Minimal Distortion ◽  
Distortion Effect ◽  
Dct Coefficients ◽  
Block Entropy ◽  
Block Complexity ◽  
Embedding Distortion ◽  
Significant Superiority

Minimizing the embedding impact is a practically feasible philosophy in designing steganographic systems. The development of steganographic systems can be formulated as the construction of distortion profile reflecting the embedding impact and the design of syndrome coding based on a certain code. The authors devise a new distortion profile exploring both the block complexity and the distortion effect due to flipping and rounding errors, and incorporate it in the framework of syndrome trellis coding (STC) to propose a new JPEG steganographic scheme. The STC provides multiple candidate solutions to embed messages to a block of coefficients while the constructed content-adaptive distortion profile guides the determination of the best solution with minimal distortion effect. The total embedding distortion or impact would be significantly reduced and lead to the less detectability of steganalysis. Extensive experimental results demonstrate that the proposed JPEG steganographic scheme greatly increases the secure embedding capacity against steganalysis and shows significant superiority over some existing JPEG steganographic approaches.

Study on Data Compression Algorithm Based on Semantic Analysis

2013 ◽  
Vol 842 ◽  
pp. 712-716
Author(s):  
Qi Hong ◽  
Xiao Lei Lu
Keyword(s):  
Data Compression ◽  
Semantic Analysis ◽  
Traditional Approach ◽  
Basic Element ◽  
Compression Algorithm ◽  
Huffman Coding ◽  
Text Compression ◽  
C Language ◽  
Lossless Data Compression ◽  
Compression Coding

As a lossless data compression coding, Huffman coding is widely used in text compression. Nevertheless, the traditional approach has some deficiencies. For example, same compression on all characters may overlook the particularity of keywords and special statements as well as the regularity of some statements. In terms of this situation, a new data compression algorithm based on semantic analysis is proposed in this paper. The new kind of method, which takes C language keywords as the basic element, is created for solving the text compression of source files of C language. The results of experiment show that the compression ratio has been improved by 150 percent roughly in this way. This method can be promoted to apply to text compression of the constrained-language.

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