Histogram-based method for image contrast enhancement

Yelmanova, Elena; Romanyshyn, Yuriy

doi:10.1109/cadsm.2017.7916105

Cited by 9 publications

(3 citation statements)

References 7 publications

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“…erefore, the HSI model has been widely used in the image representation and processing system of the human visual perception system. In the HSI model, the color is only related to the "H" and "S" components [26]. Compared with the RGB model, in the HSI model, the correlation degree of each component is relatively small [29].…”

Section: E Hsi Modelmentioning

confidence: 99%

“…Histogram equalization also known as histogram flattening is a nonlinear stretching of images and redistribution of image pixel values such that the number of pixel values in a certain gray range is roughly the same [26]. e image histogram is relatively flat by enhancing the contrast of the peak portion and reducing the contrast of the valley portions on both sides.…”

Section: Histogram Equalizationmentioning

confidence: 99%

“…Section 3 presents an analysis of the results obtained in the specific experimental environment. Section 4 concludes this paper [26].…”

Section: Introductionmentioning

confidence: 98%

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Application of Histogram Equalization for Image Enhancement in Corrosion Areas

Xiong

Wang

et al. 2021

Shock and Vibration

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In this paper, an image enhancement algorithm is presented for identification of corrosion areas and dealing with low contrast present in shadow areas of an image. This algorithm uses histogram equalization processing under the hue-saturation-intensity model. First of all, an etched image is transformed from red-green-blue color space to hue-saturation-intensity color space, and only the luminance component is enhanced. Then, part of the enhanced image is combined with the original tone component, followed by saturation and conversion to red-green-blue color space to obtain the enhanced corrosion image. Experimental results show that the proposed method significantly improves overall brightness, increases contrast details in shadow areas, and strengthens identification of corrosion areas in the image.

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Section: E Hsi Modelmentioning

confidence: 99%

Section: Histogram Equalizationmentioning

confidence: 99%