Histogram Equalization for Image Enhancement Using MRI Brain Images

Senthilkumaran, N.; Thimmiaraja, J.

doi:10.1109/wccct.2014.45

Cited by 110 publications

(43 citation statements)

References 2 publications

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“…Histogram Figure 6 The visual process of contrast correction of the proposed method. equalization (HE) (Singhai and Rawat 2007;Yeganeh et al 2008;Senthilkumaran and Thimmiaraja 2014;Arici et al 2009) will be also used in comparison as it is the basic technique in histogram modification that most commonly used by previous researchers in image processing. The proposed method is designed to improve the underwater image in terms of contrast, noise reduction, and image details, quantitative measurement such as entropy, mean square error (MSE), and peak signal to noise ratio (PSNR) are used to evaluate the output image.…”

Section: Resultsmentioning

confidence: 99%

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

Ghani

Isa

2014

2014 IEEE Fourth International Conference on Consumer Electronics Berlin (ICCE-Berlin)

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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.

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Section: Resultsmentioning

confidence: 99%

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

Ghani

Isa

2014

2014 IEEE Fourth International Conference on Consumer Electronics Berlin (ICCE-Berlin)

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“…Along with the numerous techniques of contrast enhancement, the Histogram Equalization (HE) based method is one of the most preferable techniques used by most researchers to enhance the image contrast [7][8] [9]. In Senthilkumaran et.al [10], compare different enhancement algorithms based on HE such as GHE, LHE, BPDHE and Adaptive HE. The outcome of all the comparison methods has depicted certain amount of enhancement.…”

Section: Literature Surveymentioning

confidence: 99%

Brain MR Image Enhancement using Average Intensity Replacement Based on GWOHE Algorithm

N.,

2020

IJEAT

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The most important task in MR Image Enhancement is to obtain a high resolution optimized visual image using advanced image processing techniques. Most of the life photographs and various images such as aerial, medical and satellite are associated with noise and low grade intensity. To improve the quality for better visual appearance, noise has to be suppressed and contrast has to be enhanced. Traditional contrast improvement techniques do best for various images. But for MRI of brain images, there are chances of misrecognization of WMH (White Matter Hyperintensities) as Cerebrospinal fluid (CSF) in traditional enhancement techniques. To overcome this ambiguity and enhance WMH regions of MRI brain images, a novel algorithm has been proposed in this paper. This algorithm is called as Mean Intensity replacement based on Grey Wolf Optimization Histogram Equalization (GWOHE). This technique is applied on FLAIR images and comparison is tabulated along with existing technique for parameters such as PSNR, AMBE.

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“…Brightness gene symbolizes very low frequencies inside Fourier convert on the impression along with coefficient of reflection component presents substantial wavelengths. Through increasing number these factors abject wavelengths usually are suppressed [5] distinct this brightness as well as coefficient of reflection elements through the logarithm of the impression. The particular logarithm switches your multiplicative in a great component a single.…”

Section: A Homomorphic Filteringmentioning

confidence: 99%

Underwater Image Enhancement Techniques: A Review

Madhumatke¹

2017

IJRASET

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Underwater images mainly suffer from the problem of poor color contrast and poor visibility. These problems occurred due to the scattering of light and refraction of light while entering from rarer to denser medium. Scattering causes the blurring of light and reduces the color contrast. These effects of water on underwater images are only not due the nature water but also because of the organisms and other material present in the water. Image enhancement is the process of improving the quality of the input image so that it would be easily understood by viewers in the future. Image enhancement improves the information content of the image and alters the visual impact of the image on the observer. Image enhancement intensifies the features of images. It accentuates the image features like edges, contrast to build display of photographs more useful for examination and study. Active range of the chosen features of images is amplified by enhancement so that they can be detected simply. Many techniques and methods are established by researchers to solve the problem of underwater image enhancement. In this work different underwater image enhancing techniques have been studied. Keywords: Homomorphic Filtering, Histogram Equalization, Bilateral filtering, Contrast Stretching, CLAHE I. INTRODUCTIONFrom last few years, underwater image processing area has received a great attention of researchers to explore the mysterious underwater world. Underwater surveys have numerous scientific applications in the field of archaeology, geology and biology, involving tasks such as ancient shipwreck prospection, environmental damage assessment etc. To capture a clear underwater image has a crucial importance in oceanic engineering [1]. Clear underwater images have a great importance in scientific operations like taking a census of sea population, include the discovery of objects in liquids or the image analysis needed to identify targets submerged in a liquid. There have also been studied that attempted to identify targets suspended in a solution. These studies could be useful for defense applications. For capturing a clear visible underwater image, water must be a limpid or clear, but naturally all the water is turbid with particles such as sand, planktonsor , minerals. As outdoor images are distorted because of particles present in the air, like that underwater images also get distorted because of particles present in the water. Underwater Images becomes more and more hazy or less visible as water depth increases. Generally underwater images get distorted because of two reasons. One is light scattering effect and second is color change effect. Therefore, the processing of underwater image captured is necessary because the quality of underwater images affect and these image leads due to low contrast, poor visibility conditions (absorption of natural light), non uniform lighting and little color variations, pepper noise and blur effect in the underwater images because of all these reasons number of methods are existing to cure...

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Histogram Equalization for Image Enhancement Using MRI Brain Images

Cited by 110 publications

References 2 publications

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

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

Brain MR Image Enhancement using Average Intensity Replacement Based on GWOHE Algorithm

Underwater Image Enhancement Techniques: A Review

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