An improved lossless image compression based arithmetic coding using mixture of non-parametric distributions

Puech, William; Masmoudi, Afif

doi:10.1007/s11042-014-2195-8

Cited by 19 publications

(15 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Arithmetic coding as a lossless compression mechanism presumes a clear probabilistic model of the input and performs almost optimum compression with the provided probability estimation [30]. AC encodes the whole input into a singular numeral, a fraction n where 0 ≤ n < 1.0.…”

Section: Proposed Partial Encryption–compression Schemementioning

confidence: 99%

Secure image compression approach based on fusion of 3D chaotic maps and arithmetic coding

Darwish

Noori²

2019

IET signal process.

View full text Add to dashboard Cite

Advances in digital image processing and communications have created a great demand for real‐time secure image transmission over the networks. However, the development of effective, fast and secure dependent image compression‐encryption systems are still a research problem as the intrinsic features of images. A new approach is suggested in this study for partial image encryption‐compression that adopts chaotic three‐dimensional (3D) cat map to de‐correlate relations among pixels in conjunction with an adaptive thresholding technique that is utilised as a lossy compression technique instead of using complex quantisation techniques and also as a substitution technique to increase the security of the cipher image. The proposed scheme is based on employing both of lossless compression with encryption on the most significant part of the image after contourlet transform. However, the least significant parts are lossy compressed by employing a simple thresholding rule and arithmetic coding to render the image totally unrecognisable. Due to the weakness of 3D cat map to chosen plain text attack, the suggested scheme incorporates a mechanism to generate random key depending on the contents of the image (context key). Several experiments were done on benchmark images to insure the validity of the proposed technique.

show abstract

Section: Proposed Partial Encryption–compression Schemementioning

confidence: 99%

Secure image compression approach based on fusion of 3D chaotic maps and arithmetic coding

Darwish

Noori²

2019

IET signal process.

View full text Add to dashboard Cite

show abstract

“…Therefore, the basic idea was to apply the histogram packing on consecutive image blocks which provides the ability to explore the non stationary local characteristics. Several studies have confirmed that encoding on block-basis provide additional improvements particularly for images with locally sparse histograms [16]- [18]. However, the increase in the number of blocks leads to a compression efficiency loss since the total overhead generated by block-based histogram packing methods depends on the number of image blocks and the size of the mapping table.…”

Section: Histogram Packingmentioning

confidence: 99%

A preprocessing technique for improving the compression performance of JPEG 2000 for images with sparse or locally sparse histograms

Jallouli

Zouari

Masmoudi

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

Self Cite

View full text Add to dashboard Cite

Abstract-JPEG 2000 is one of the most efficient and well performing standards for continuous-tone natural images compression. However, a compression performance loss may occur when encoding images with sparse or locally sparse histograms. Images of the later type include only a subset of the available intensity values implied by the nominal alphabet. This article proposes a new adaptive block-based histogram packing which improves the lossless compression performance of JPEG 2000 with sparse histogram images. We take advantage, in this work, of the strength likelihood between symbol sets of the neighboring image blocks and the efficiency of the offline histogram packing with sparse or locally sparse histogram images. Results of its effectiveness with JPEG 2000 are presented.Index Terms-lossless image compression; offline histogram packing; JPEG 2000; alphabet reduction scheme; sparse and locally sparse histograms.

show abstract

“…As a result, around 15.5% and 16.4% bitrates are decremented for static and adaptive order sequentially. Utilizing adaptive arithmetic coding and finite mixture models, a block-predicated lossless compression has been proposed in [31]. Here, an image is partitioned into non-overlapping blocks and encoded every block individually utilizing arithmetic coding.…”

Section: Introductionmentioning

confidence: 99%

Lossless Image Compression Techniques: A State-of-the-Art Survey

Rahman

Hamada

2019

Symmetry

View full text Add to dashboard Cite

Modern daily life activities result in a huge amount of data, which creates a big challenge for storing and communicating them. As an example, hospitals produce a huge amount of data on a daily basis, which makes a big challenge to store it in a limited storage or to communicate them through the restricted bandwidth over the Internet. Therefore, there is an increasing demand for more research in data compression and communication theory to deal with such challenges. Such research responds to the requirements of data transmission at high speed over networks. In this paper, we focus on deep analysis of the most common techniques in image compression. We present a detailed analysis of run-length, entropy and dictionary based lossless image compression algorithms with a common numeric example for a clear comparison. Following that, the state-of-the-art techniques are discussed based on some bench-marked images. Finally, we use standard metrics such as average code length (ACL), compression ratio (CR), pick signal-to-noise ratio (PSNR), efficiency, encoding time (ET) and decoding time (DT) in order to measure the performance of the state-of-the-art techniques.

show abstract

An improved lossless image compression based arithmetic coding using mixture of non-parametric distributions

Cited by 19 publications

References 25 publications

Secure image compression approach based on fusion of 3D chaotic maps and arithmetic coding

Secure image compression approach based on fusion of 3D chaotic maps and arithmetic coding

A preprocessing technique for improving the compression performance of JPEG 2000 for images with sparse or locally sparse histograms

Lossless Image Compression Techniques: A State-of-the-Art Survey

Contact Info

Product

Resources

About