Depth Estimation Based Underwater Image Enhancement

2014 ◽  
Vol 926-930 ◽  
pp. 1704-1707
Author(s):  
Qiu Yun Wang
Keyword(s):  
Image Enhancement ◽  
Image Data ◽  
Depth Estimation ◽  
Dark Channel Prior ◽  
Prior Model ◽  
Color Distortion ◽  
Underwater Image ◽  
Good Ability ◽  
Dark Channel

According to the image formation model and the nature of underwater images, we find that the effect of the haze and the color distortion seriously pollute the underwater image data, lowing the quality of the underwater images in the visibility and the quality of the data. Hence, aiming to reduce the noise and the haze effect existing in the underwater image and compensate the color distortion, the dark channel prior model is used to enhance the underwater image. We compare the dark channel prior model based image enhancement method to the contrast stretching based method for image enhancement. The experimental results proved that the dark channel prior model has good ability for processing the underwater images. The super performance of the proposed method is demonstrated as well.

scholarly journals Research on underwater image enhancement algorithm based on improved DCP

2021 ◽  
Vol 2083 (4) ◽  
pp. 042008
Author(s):  
Zhe Wu ◽  
Jianfgui Han ◽  
Chenghao Cao
Keyword(s):  
Image Enhancement ◽  
Transfer Rate ◽  
Color Correction ◽  
Dark Channel Prior ◽  
Underwater Image ◽  
Depth Analysis ◽  
Dark Channel ◽  
Color Bias ◽  
Enhancement Algorithm ◽  
Priority Algorithm

Abstract All for underwater images, there are some drawbacks, such as low definition, serious color bias, dark brightness, etc. On the basis of in-depth analysis of common image enhancement algorithms, This paper uses the improved dark channel priority algorithm to enhance the underwater image, Improving the contrast of underwater images and color correction of underwater images. Color correction is added based on dark channel prior algorithm; Make the image look more even, higher contrast, more acceptable. The improved algorithm model has a higher transfer rate; PSNR is more balanced and has better contrast to meet the requirements of underwater image observation.

scholarly journals Underwater Image Enhancement Method Based On Color Correction and Dark Channel Prior

2021 ◽  
Vol 2066 (1) ◽  
pp. 012050
Author(s):  
Hao Chen ◽  
Hongsen He ◽  
Xinghua Feng
Keyword(s):  
Image Enhancement ◽  
Color Correction ◽  
Dark Channel Prior ◽  
Low Contrast ◽  
Underwater Environment ◽  
Underwater Image ◽  
Blue Channel ◽  
Dark Channel ◽  
Green Background ◽  
Enhancement Method

Abstract Concerning to the problem in the distortion of color and the low contrast of underwater image, the image enhancement method in the underwater environment based on color correction and dark channel prior was proposed. When dealing with the color bias problem, the blue channel standard ratio is firstly calculated based on the blue channel, and the red and green channels of the underwater image are compensated to remove the blue and green background colors of the underwater image. In light of the problem in the low contrast of image in underwater environment, the dark channel prior (DCP) method based on the super pixel was used to enhance the corrected underwater image. Finally, the underwater object detection dataset images are tested, and the algorithm proposed in terms of the quality is made the comparison with six advanced image enhancement method in underwater environment. The experimental results show that the proposed algorithm earned the highest score in underwater quality evaluation index (UIQM) compared with the above algorithm.

scholarly journals Underwater image enhancement algorithm based on dark channel prior and underwater imaging model

2021 ◽  
Vol 336 ◽  
pp. 06033
Author(s):  
Zhengping Sun ◽  
Fubing Li ◽  
Yuying Yang
Keyword(s):  
Image Enhancement ◽  
Dark Channel Prior ◽  
Underwater Imaging ◽  
Low Contrast ◽  
Underwater Environment ◽  
Imaging Model ◽  
Underwater Image ◽  
Dark Channel ◽  
Color Compensation ◽  
Enhancement Method

The main reason for the degradation of the underwater image is the light absorption and scattering. The images are captured in the underwater environment often have some problems such as loss of image information, low contrast, and color distortion. In order to solve the above problems, this paper proposes an image enhancement method for the underwater environment. With the help of the underwater imaging model and dark channel prior theory, a new idea of adding transmission correction and color compensation to G and B color channels is proposed. Experimental results show that, compared with the traditional methods, this method has a better effect on the underwater image with less color deviation.

scholarly journals Underwater Image Enhancement Using Successive Color Correction and Superpixel Dark Channel Prior

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1220 ◽  
Author(s):  
Ho Sang Lee ◽  
Sang Whan Moon ◽  
Il Kyu Eom
Keyword(s):  
Image Enhancement ◽  
Correction Method ◽  
Color Correction ◽  
Water Medium ◽  
Dark Channel Prior ◽  
Low Contrast ◽  
White Balance ◽  
Underwater Image ◽  
Corrected Image ◽  
Dark Channel

Underwater images generally suffer from quality degradations, such as low contrast, color cast, blurring, and hazy effect due to light absorption and scattering in the water medium. In applying these images to various vision tasks, single image-based underwater image enhancement has been challenging. Thus, numerous efforts have been made in the field of underwater image restoration. In this paper, we propose a successive color correction method with a minimal reddish artifact and a superpixel-based restoration using a color-balanced underwater image. The proposed successive color correction method comprises an effective underwater white balance based on the standard deviation ratio, followed by a new image normalization. The corrected image based on this color balance algorithm barely produces a reddish artifact. The superpixel-based dark channel prior is exploited to enhance the color-corrected underwater image. We introduce an image-adaptive weight factor using the mean of backscatter lights to estimate the transmission map. We perform intensive experiments for various underwater images and compare the performance of the proposed method with those of 10 state-of-the-art underwater image-enhancement methods. The simulation results show that the proposed enhancement scheme outperforms the existing approaches in terms of both subjective and objective quality.

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