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

Ghani, Ahmad Shahrizan Abdul; Isa, Nor Ashidi Mat

doi:10.1109/icce-berlin.2014.7034265

Cited by 37 publications

(32 citation statements)

References 18 publications

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“…The results are illustrated with images of fishes and marine flora captured in the foreground. The HSV color space has been also used more recently in a twostage method (Ghani et al, 2014), for enhancing of coral images. First, the contrast correction technique is applied to the image with a modified Von Kries hypothesis and stretching it into two different intensity images at the average value with respect to Rayleigh distribution.…”

Section: Related Workmentioning

confidence: 99%

A New Color Correction Method for Underwater Imaging

Bianco

Muzzupappa

Bruno

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Recovering correct or at least realistic colors of underwater scenes is a very challenging issue for imaging techniques, since illumination conditions in a refractive and turbid medium as the sea are seriously altered. The need to correct colors of underwater images or videos is an important task required in all image-based applications like 3D imaging, navigation, documentation, etc. Many imaging enhancement methods have been proposed in literature for these purposes. The advantage of these methods is that they do not require the knowledge of the medium physical parameters while some image adjustments can be performed manually (as histogram stretching) or automatically by algorithms based on some criteria as suggested from computational color constancy methods. One of the most popular criterion is based on gray-world hypothesis, which assumes that the average of the captured image should be gray. An interesting application of this assumption is performed in the Ruderman opponent color space lαβ, used in a previous work for hue correction of images captured under colored light sources, which allows to separate the luminance component of the scene from its chromatic components. In this work, we present the first proposal for color correction of underwater images by using lαβ color space. In particular, the chromatic components are changed moving their distributions around the white point (white balancing) and histogram cutoff and stretching of the luminance component is performed to improve image contrast. The experimental results demonstrate the effectiveness of this method under gray-world assumption and supposing uniform illumination of the scene. Moreover, due to its low computational cost it is suitable for real-time implementation.

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Section: Related Workmentioning

confidence: 99%

A New Color Correction Method for Underwater Imaging

Bianco

Muzzupappa

Bruno

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…In Schoening et al (2012a) it was for instance shown, how the object distance to the centroid of the illumination cone influences the observers decision. A variety of algorithms have been developed to enhance underwater images by (a) dehazing the image (Trucco and Olmos-Antillon, 2006;Ancuti et al, 2012;Chiang and Chen, 2012), (b) compensating non-uniform illumination (Eustice et al, 2002;Singh et al, 2007;Schoening et al, 2012b;Bryson et al, 2015) and (c) increasing the image contrast and correcting the color shift (Zuiderveld, 1994;Eustice et al, 2002;Chambah et al, 2003;Trucco and Olmos-Antillon, 2006;Singh et al, 2007;Petit et al, 2009;Iqbal et al, 2010;Ancuti et al, 2012;Chiang and Chen, 2012;Schoening et al, 2012b;Abdul Ghani and Mat Isa, 2014;Bryson et al, 2015). Although in the last years new methods have been proposed to compare and rank the quality of different algorithms (Osterloff et al, 2014;Panetta et al, 2015;Yang and Sowmya, 2015), the selection of the best algorithm can be challenging.…”

Section: Introductionmentioning

confidence: 99%

RecoMIA—Recommendations for Marine Image Annotation: Lessons Learned and Future Directions

2016

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Marine imaging is transforming into a sensor technology applied for high throughput sampling. In the context of habitat mapping, imaging establishes thereby an important bridge technology regarding the spatial resolution and information content between physical sampling gear (e.g., box corer, multi corer) on the one end and hydro-acoustic sensors on the other end of the spectrum of sampling methods. In contrast to other scientific imaging domains, such as digital pathology, there are no protocols and reports available that guide users (often referred to as observers) in the non-trivial process of assigning semantic categories to whole images, regions, or objects of interest (OOI), which is referred to as annotation. These protocols are crucial to facilitate image analysis as a robust scientific method. In this article we will review the past observations in manual Marine Image Annotations (MIA) and provide (a) a guideline for collecting manual annotations, (b) definitions for annotation quality, and (c) a statistical framework to analyze the performance of human expert annotations and to compare those to computational approaches.

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“…The scattering of light is wavelength dependent so for correction of nonuniform illumination each color component (R, G, B) should be processed separately. While providing solution for nonuniform illumination, the method assumes that the underwater images are Rayleigh distributed [4][5][6]. Consider…”

Section: Introductionmentioning

confidence: 99%

Nonuniform Illumination Correction Algorithm for Underwater Images Using Maximum Likelihood Estimation Method

Sankpal¹,

Deshpande²

2016

Journal of Engineering

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Scattering and absorption of light is main reason for limited visibility in water. The suspended particles and dissolved chemical compounds in water are also responsible for scattering and absorption of light in water. The limited visibility in water results in degradation of underwater images. The visibility can be increased by using artificial light source in underwater imaging system. But the artificial light illuminates the scene in a nonuniform fashion. It produces bright spot at the center with the dark region at surroundings. In some cases imaging system itself creates dark region in the image by producing shadow on the objects. The problem of nonuniform illumination is neglected by the researchers in most of the image enhancement techniques of underwater images. Also very few methods are discussed showing the results on color images. This paper suggests a method for nonuniform illumination correction for underwater images. The method assumes that natural underwater images are Rayleigh distributed. This paper used maximum likelihood estimation of scale parameter to map distribution of image to Rayleigh distribution. The method is compared with traditional methods for nonuniform illumination correction using no-reference image quality metrics like average luminance, average information entropy, normalized neighborhood function, average contrast, and comprehensive assessment function.

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

Cited by 37 publications

References 18 publications

A New Color Correction Method for Underwater Imaging

A New Color Correction Method for Underwater Imaging

RecoMIA—Recommendations for Marine Image Annotation: Lessons Learned and Future Directions

Nonuniform Illumination Correction Algorithm for Underwater Images Using Maximum Likelihood Estimation Method

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