Near-lossless image compression using an improved edge adaptive hierarchical interpolation

<span>In medical and scientific imaging, lossless image compression is recommended because the loss of minor details subject to medical diagnosis can lead to wrong diagniosis. On the other hand, lossy compression of medical images is required in the long run because a huge quantity of medical data needs remote storage. This, in turn, takes long time to search and transfer an image. Instead of thinking lossless or lossy image compression methods, near-loss image compression mehod can be used to compromise the two conflicting requirements. In the previous work, an edge adaptive hierarchical interpolation (EAHINT) was proposed for resolution scalable lossless compression of images. In this paper, it was enhanced for scalable near-less image compression. The interpolator of this arlgorithm swiches among one-directional, multi-directional and non-directional linear interpolators adaptively based on the strength of the edge in a 3x3 local casual context of the current pixel being predicted. The strength of the edge in local window was estimated using the variance of the the pixels in the local window. Although the actual predictors are still linear functions, the switching mechanism tried to deal with non-linear structures like edges. Simulation results demonstrate that the improved interpolation algorithm has better compression ratio over the the exsisting the original EAHINT algorithm and JPEG-Ls image compression standard. </span>

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Joint Lossless Image Compression and Encryption Scheme Based on CALIC and Hyperchaotic System

Entropy ◽

10.3390/e23081096 ◽

2021 ◽

Vol 23 (8) ◽

pp. 1096

Author(s):

Miao Zhang ◽

Xiaojun Tong ◽

Zhu Wang ◽

Penghui Chen

Keyword(s):

Image Compression ◽

Lossless Compression ◽

Image Transmission ◽

Single Step ◽

Hyperchaotic System ◽

Encryption Scheme ◽

Lossless Image Compression ◽

Compression Performance ◽

Final Prediction Error ◽

Image Compression And Encryption

For efficiency and security of image transmission and storage, the joint image compression and encryption method that performs compression and encryption in a single step is a promising solution due to better security. Moreover, on some important occasions, it is necessary to save images in high quality by lossless compression. Thus, a joint lossless image compression and encryption scheme based on a context-based adaptive lossless image codec (CALIC) and hyperchaotic system is proposed to achieve lossless image encryption and compression simultaneously. Making use of the characteristics of CALIC, four encryption locations are designed to realize joint image compression and encryption: encryption for the predicted values of pixels based on gradient-adjusted prediction (GAP), encryption for the final prediction error, encryption for two lines of pixel values needed by prediction mode and encryption for the entropy coding file. Moreover, a new four-dimensional hyperchaotic system and plaintext-related encryption based on table lookup are all used to enhance the security. The security tests show information entropy, correlation and key sensitivity of the proposed methods reach 7.997, 0.01 and 0.4998, respectively. This indicates that the proposed methods have good security. Meanwhile, compared to original CALIC without security, the proposed methods increase the security and reduce the compression ratio by only 6.3%. The test results indicate that the proposed methods have high security and good lossless compression performance.

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The Problem of Identifying and Modeling the Relationship between Monetary Factor and Inflation in the Russian Economy

Voprosy Ekonomiki ◽

10.32609/0042-8736-2008-7-61-76 ◽

2008 ◽

pp. 61-76

Author(s):

A. Porshakov ◽

A. Ponomarenko

Keyword(s):

Money Supply ◽

Money Demand ◽

Russian Economy ◽

Long Run ◽

Complex Approach ◽

Wide Range ◽

Long Time ◽

The Relationship ◽

Supply Side Factors

The role of monetary factor in generating inflationary processes in Russia has stimulated various debates in social and scientific circles for a relatively long time. The authors show that identification of the specificity of relationship between money and inflation requires a complex approach based on statistical modeling and involving a wide range of indicators relevant for the price changes in the economy. As a result a model of inflation for Russia implying the decomposition of inflation dynamics into demand-side and supply-side factors is suggested. The main conclusion drawn is that during the recent years the volume of inflationary pressures in the Russian economy has been determined by the deviation of money supply from money demand, rather than by money supply alone. At the same time, monetary factor has a long-run spread over time impact on inflation.

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