A Review of DNA Microarray Image Compression

́ndez-Cabronero, Miguel Hern; Blanes, Ian; Serra-Sagristà, Joan; Marcellin, Michael W.

doi:10.1109/ccp.2011.21

Cited by 5 publications

(3 citation statements)

References 34 publications

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“…Results presented in Table 2 and Table 3 are normalized with respect to the Weighted Average results of under the column BWIC. In Table 4 microarray-specific compressors results retrieved from [11] are given.…”

Section: B Resultsmentioning

confidence: 99%

“…They showed that the Burrows-Wheeler Transformation[10] helps to reduce the total entropy and improves the compression gain for microarray image data. Further details about other proposed compression techniques in compression of microarray images can be found in the review paper of Hernndez-Cabronero et al in[11]. This paper is organized as follows: In section 2, we briefly explain the Burrows-Wheeler Transformation and Inversion Coder.…”

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Lossless compression of DNA Microarray images with Inversion Coder

Koc¹,

Arnavut²,

Koçak³

2014

2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)

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DNA Microarray images are used to identify and monitor gene activity, or expression. In a single experiment, a large number of microarray images may be produced. Storage and archiving of these images are an important problem for researchers. Since microarray images can have a wide variety of nearly random patterns with no discernible structures, general entropy coders, e.g. Bzip2, or generic image compressors, e.g. JPEG-LS, do not perform well. In this work, we investigate performance of the inversion coding technique in lossless com pression of DNA microarray images. We show that inversion coding outperforms commonly used entropy coders and image compressors.

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Section: B Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

Lossless compression of DNA Microarray images with Inversion Coder

Koc¹,

Arnavut²,

Koçak³

2014

2014 11th Annual High Capacity Optical Networks and Emerging/Enabling Technologies (Photonics for Energy)

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show abstract

“…While Pinho et al tested only the JJ2000 implementation using the default parameter selections of DWT, with 5 decomposition levels and 33 quality layers, we have also evaluated the performance with 0 to 5 decomposition levels and the same number of quality layers with both the JJ2000 and Kakadu implementations. We show in Table 6 an updated version of the data that we have previously provided [49]. As in the case of the general compression schemes, results are obtained by dividing the total number of bits of the compressed images by the total number of pixels of the original images.…”

Section: Image Compression Standardsmentioning

confidence: 99%

Standard and Specific Compression Techniques for DNA Microarray Images

et al. 2012

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We review the state of the art in DNA microarray image compression and provide original comparisons between standard and microarray-specific compression techniques that validate and expand previous work. First, we describe the most relevant approaches published in the literature and classify them according to the stage of the typical image compression process where each approach makes its contribution, and then we summarize the compression results reported for these microarray-specific image compression schemes. In a set of experiments conducted for this paper, we obtain new results for several popular image coding techniques that include the most recent coding standards. Prediction-based schemes CALIC and JPEG-LS are the best-performing standard compressors, but are improved upon by the best microarray-specific technique, Battiato’s CNN-based scheme

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Microarray Image Lossless Compression Using General Entropy Coders and Image Compression Standards

Joseph

Sathidevi

2023

Circuits Syst Signal Process

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A Review of DNA Microarray Image Compression

Cited by 5 publications

References 34 publications

Lossless compression of DNA Microarray images with Inversion Coder

Lossless compression of DNA Microarray images with Inversion Coder

Standard and Specific Compression Techniques for DNA Microarray Images

Microarray Image Lossless Compression Using General Entropy Coders and Image Compression Standards

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