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Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching

Overview of attention for article published in SpringerPlus, December 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
38 Mendeley
Title
Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching
Published in
SpringerPlus, December 2014
DOI 10.1186/2193-1801-3-757
Pubmed ID
Authors

Ahmad Shahrizan Abdul Ghani, Nor Ashidi Mat Isa

Abstract

The quality of underwater image is poor due to the properties of water and its impurities. The properties of water cause attenuation of light travels through the water medium, resulting in low contrast, blur, inhomogeneous lighting, and color diminishing of the underwater images. This paper proposes a method of enhancing the quality of underwater image. The proposed method consists of two stages. At the first stage, the contrast correction technique is applied to the image, where the image is applied with the modified Von Kries hypothesis and stretching the image into two different intensity images at the average value with respects to Rayleigh distribution. At the second stage, the color correction technique is applied to the image where the image is first converted into hue-saturation-value (HSV) color model. The modification of the color component increases the image color performance. Qualitative and quantitative analyses indicate that the proposed method outperforms other state-of-the-art methods in terms of contrast, details, and noise reduction.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 34%
Researcher 4 11%
Student > Master 3 8%
Student > Bachelor 2 5%
Lecturer 2 5%
Other 5 13%
Unknown 9 24%
Readers by discipline Count As %
Engineering 15 39%
Computer Science 8 21%
Medicine and Dentistry 1 3%
Decision Sciences 1 3%
Unknown 13 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2014.
All research outputs
#4,168,867
of 22,778,347 outputs
Outputs from SpringerPlus
#253
of 1,852 outputs
Outputs of similar age
#59,231
of 353,195 outputs
Outputs of similar age from SpringerPlus
#16
of 76 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,195 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.