Enhancing Visibility of Polarimetric Underwater Image by Transmittance Correction

Hu, Haofeng; Zhao, Lin; Huang, Bingjing; Li, Xiaobo; Wang, Hui; Liu, Tiegen

doi:10.1109/jphot.2017.2698000

Cited by 40 publications

(22 citation statements)

References 23 publications

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“…4(b) , the range of gray level of the intensity image is compressed into a narrow band. Here we introduce the measure of enhancement (EME) to quantify the image quality 25 , 26 as follows: where the image i ( x, y ) is divided into m × n blocks , and refer to the max- and min-value of the image in the block . In order to avoid being divided by zero, the parameter q is a small constant set to 0.0001 25 .…”

Section: Resultsmentioning

confidence: 99%

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Polarimetric image recovery method combining histogram stretching for underwater imaging

Zhao

et al. 2018

Sci Rep

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The underwater imaging could be severely degraded by the scattering media because of the backscattered light and signal attenuation, especially in the case of strong scattering for dense turbid medium. In this paper, we propose an improved method for recovering the underwater image combining the histogram stretching and polarimetric recovery in a proper way. In this method, we stretch the histograms of the orthogonal polarization images while maintaining the polarization relation between them, and then, based on the processed orthogonal polarization images, the recovered image with higher quality can be obtained by the traditional polarimetric recovery method. Several groups of experimental results demonstrate that the quality of underwater images can be effectively enhanced by our method, and its performance is better than that of the traditional polarimetric recovery method. In particular, the proposed method is also quite effective in the condition of dense turbid medium.

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Section: Resultsmentioning

confidence: 99%

“… 17 , 18 is found to be an effective way to enhance the quality of hazy images in turbid medium, which recovers the image based on two images captured at orthogonal polarization states. Based on Schechner’s method, various improved methods have been proposed to recovery the hazy images 19 – 26 . For example, Liang et al .…”

Section: Introductionmentioning

confidence: 99%

Polarimetric image recovery method combining histogram stretching for underwater imaging

Zhao

et al. 2018

Sci Rep

Self Cite

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“…A feasible strategy is by using active illumination. Furthermore, many previous literatures [11], [18], [24] have proven that the polarized illumination can increase the DOP of the scene, which is benefit for the further improvement of the recovery performance. The corresponding experimental setup is shown in Fig.…”

Section: Underwater Imaging Experimentsmentioning

confidence: 99%

Pseudo-polarimetric Method for Dense Haze Removal

Zhao

et al. 2019

IEEE Photonics J.

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The scattering and absorption by the existing particles in turbid media is severely degrading the image quality and decreasing the visibility distance, especially in dense turbid media. In this paper, we investigate the polarization property of hazy images in dense turbid media, and we propose a simple pseudo-polarimetric dehazing method for dense haze removal, which only requires a single image captured by the detector. By our proposed method, two orthogonal polarization subimages are derived from the single original image, and then, based on these two subimages, one can obtain the recovered image by using the traditional polarimetric method. The real-word experimental results verify that, for the dense haze, our method based on a single image could have a comparable or better performance compared to the traditional polarimetric dehazing method with multiple images captured at different polarization states.

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“…Hu et al [10] published a study for enhancing the resolution of underwater images with the purpose of correction in motion transfer.…”

Section: Introductionmentioning

confidence: 99%

“…Image quality restoration has also been one of the developed techniques by Wang et al [11] as well as another researcher in [12] where identifying the attenuation of the image. Similar to [10][11][12], another study has conducted in recovering the underwater images based on blurriness in addition to light absorption [13]. This manner actually enhanced the image processing.…”

Section: Introductionmentioning

confidence: 99%

A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

Moghimi

Mohanna

2019

SN Appl. Sci.

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Nowadays, the underwater optical imaging is used by a wide range of sciences including marine scientists for studying underwater structures and organisms, oil and gas companies, telecommunications to monitor fuel transmission lines and cables, and military centers to detect the sea mines and submarines. Images with non-uniform brightness are visually limited due to low ambient light during imaging or excessive exposure, fogging, hazing, or a combination of these factors. As a result, a process of imaging improvement is highly complex with some conditions. Particularly, this issue is harmful for the underwater environments as well as its highly complexity. In this paper, we improve the underwater images from different environments by exploiting image processing techniques including elimination of fogging in the image, and improvement of contrast with combining super resolution methods which result in significant enhancement of the image quality. To remove fogging in the image enhancement method, a variational-based fusion method was proposed without increasing or decreasing image resolution to increase the adaptability of non-uniform backlight images. This approach is optimized by the bee colony algorithm. Additionally, weighting coefficient selection method is used for super resolution of image after adjusting contrast. The main reason for using hybrid contrast techniques includes the adaptive enhancement and color correction. The bee colony algorithm and weighting coefficient in super resolution due to the lack of hybrid methods in visually improved water images has been the subject of recent researches. The hybrid set has provided more effect on different images at various conditions. Having applied the algorithm set for low-quality visual image set of underwater, some analyses such as PSNR, MSE and SSIM are tested. Compared to similar solutions, the quality is significantly improved and highlighted the exhaustive operation of the algorithm. Applying the presented algorithm in the software part of underwater imaging systems is widely effective for the accurate analysis of underwater images.

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Enhancing Visibility of Polarimetric Underwater Image by Transmittance Correction

Cited by 40 publications

References 23 publications

Polarimetric image recovery method combining histogram stretching for underwater imaging

Polarimetric image recovery method combining histogram stretching for underwater imaging

Pseudo-polarimetric Method for Dense Haze Removal

A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

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