Enhancing the low quality images using Unsupervised Colour Correction Method

Iqbal, Kashif; Odetayo, Michael O.; James, Anne; Salam, Rosalina Abdul; Talib, Abdullah Zawawi

doi:10.1109/icsmc.2010.5642311

Cited by 322 publications

(207 citation statements)

References 10 publications

(11 reference statements)

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“…However, it does not optimally increase the image contrast. Iqbal et al proposed the integrated color model (ICM) (Iqbal et al 2007) and the unsupervised color correction method (UCM) (Iqbal et al 2010). In Iqbal et al (2007), the output image in the red-green-blue (RGB) color model is stretched over the entire dynamic range.…”

Section: Introductionmentioning

confidence: 99%

“…After stretching, the image in HSI color model is then converted back into the RGB color model to produce an enhanced output image. In (Iqbal et al 2010), Iqbal et al modified two color channels, red and green, based on the Von Kries hypothesis to reduce the color cast. Contrast correction is then applied in the RGB color model.…”

Section: Introductionmentioning

confidence: 99%

“…Contrast stretching toward the upper side is applied to red, which is the lowest intensity channel. Contrast stretching at both sides is applied to green, which is the middle intensity value of the color channels, and contrast stretching at the lower side is applied to blue, which is the dominant color cast (Iqbal et al 2010). For underwater images, the image is further converted into the HSI color model, and the S and I components are stretched at both the lower and upper sides.…”

Section: Introductionmentioning

confidence: 99%

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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: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…[14] worked on "Enhancing the low quality images using Unsupervised Colour Correction Method,", The affected underwater images reduced contrast and non-uniform color cast because of the absorption and scattering of light rays in the marine environment. For that they proposed an Unsupervised Colour Correction Method (UCM) for underwater image quality enhancement.…”

Section: Literature Surveymentioning

confidence: 99%

A Survey on Underwater Image Enhancement Techniques

Sahu¹,

Gupta²,

Sharma³

2014

IJCA

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This review paper deals with the methods to improve underwater image enhancement techniques, the processing of underwater image captured is necessary because the quality of underwater images affect and these image leads some serious problems when compared to images from a clearer environment. A lot of noise occurs 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 these underwater images different filtering techniques are also available in the literature for processing and enhancement of underwater images one of them is image enhancement using median filter which enhances the image and help to estimate the depth map and improve quality by removing noise particles with the help of different techniques, and the other is RGB Color Level Stretching have used. Forward USM technique can also be used for image enhancement.

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“…The main drawback of this approach is it amplifies the noise in homogeneous regions and creates false colors. Some research lines work to palliate this problems like [Hitam et al, 2013], [Iqbal et al, 2010] and [Ghani and Isa, 2015] combining different histogram equalizations, target distributions and contrast stretching.…”

Section: State Of the Artmentioning

confidence: 99%

Visibility in underwater robotics: Benchmarking and single image dehazing

Soler¹

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A mis padres y hermanos. AcknowledgementsThis thesis is the result of more than 5 years of work and it would have been impossible without the support of family, friends and colleagues. May the reader forgive me the discourtesy of following my wish to acknowledge their support in my mother tongue.But before changing to my mother tongue, I want to thank professor Stefan Williams for hosting me at the Australian Centre for Field Robotics in Sydney for four months. Working with his group, and specially with Mitch Bryson and Dushyant Rao, was crucial for the development of the final chapters of this thesis. I also have to acknowledge the ACFR for providing and preparing the datasets used in the deep learning experiments.En primer lugar, me gustaría agradecer a mis directores Raúl Marín y Pedro Sanz la oportunidad de poder trabajar en un campo tan motivante y desafiante como la robótica submarina a través de distintos proyectos en la frontera del conocimiento como Trident, Triton o Merbots. Además de por la ayuda y los consejos desde la experiencia a la hora de introducirme en la investigación.Gracias a la Universitat Jaume I por haber financiado durante 4 años el desarrollo de esta tesis a través del plan de promoción de la investigación (referencia de la ayuda PREDOC/2012/47).También tengo que dar las gracias a todos los miembros del IRSLab de los que he podido aprender, y con los que he colaborado y trabajado como un verdadero equipo durante estos años. A todos quiero dar gracias, Juan Carlos por su disponibilidad a la hora de ayudar, Javi por su espíritu de equipo, Toni por su decisión a la hora de afrontar problemas, David por susánimos y voluntad, Jorge por su insistencia en publicar, José Bernabé por sus consejos y Diego por su entrega.Gracias también a Mario, pese al poco tiempo que coincidimos demostró ser un investigador sobresaliente y un compañero ejemplar que me ayudó en los primeros momentos de este trabajo. Además también tengo que agradecer al RobInLab, especialmente aÁngel, Carlos, Marco, Xavi, Gabriel, Majd y Gustavo, por su ayuda y discusiones en los descansos delante de una taza de café.Durante mi estancia en Sydney tuve la suerte de coincidir con un pequeño grupo de españoles que hizo la estancia mucho más amena. Por ello también quiero darles las gracias, en particular a Guillem y a Raúl con los cuales compartí mucho tiempo dentro y fuera del laboratorio visitando y conociendo Australia, y en general a todas las personas con las que coincidí durante esos meses.Gracias a mi familia y amigos de la Venta del Moro, siempre dispuestos a escuchar después de una larga semana de trabajo. Durante estos años han sido v una distracción necesaria a los problemas del día a día, haciendo el camino de esta tesis mucho más entretenido.Quiero también agradecer a Loli por ser una más de la familia y preocuparse y cuidar de mí día a día desde bien pequeño, ayudándome a convertirme en una persona mejor.Porúltimo, quiero agradecer especialmente la ayuda y el apoyo de mi familia. A mis padres Luis y MaríaÁngeles que m...

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Enhancing the low quality images using Unsupervised Colour Correction Method

Cited by 322 publications

References 10 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

A Survey on Underwater Image Enhancement Techniques

Visibility in underwater robotics: Benchmarking and single image dehazing

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