Journals / Turkish Journal of Electrical Engineering and Computer Science / 2018 / Cilt: 26 - Sayı: 1

Weighted intensity hue saturation transform for image enhancement and pansharpening

Pages
204–219
Publication Date
2018-02-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The visual and quantitative comparisons show that the proposed transform is superior to the classical IHS transform.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, a weighted intensity hue saturation transform (WIHS) is proposed for image enhancement and pansharpening.
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Key Findings & Data:The proposed transform obtains the intensity component of the classical intensity hue saturation (IHS) transform, by weighting the bands (red, green, and blue) of the image, whereas the hue and saturation components remain unchanged.
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Conclusion & Impact:The visual and quantitative comparisons show that the proposed transform is superior to the classical IHS transform.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Image enhancement · pansharpening · intensity hue saturation transform

Abstract

In this paper, a weighted intensity hue saturation transform (WIHS) is proposed for image enhancement and pansharpening. The proposed transform obtains the intensity component of the classical intensity hue saturation (IHS) transform, by weighting the bands (red, green, and blue) of the image, whereas the hue and saturation components remain unchanged. The weight for each band is determined according to the brightness interval of the corresponding band and its standard deviation. The purpose of obtaining the intensity component by weighting is to keep more information from the bands of the input image. The classical intensity component used in image processing algorithms is replaced with the proposed weighted intensity component. The visual and quantitative comparisons show that the proposed transform is superior to the classical IHS transform.

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Cite This Article

KAPLAN, N. H. (2018). Weighted intensity hue saturation transform for image enhancement and pansharpening. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 26 - Sayı: 1, 204–219. https://ajindex.com/articles/187123

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