scholarly journals Low-Light Underwater Image Enhancement for Deep-Sea Tripod

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 44080-44086 ◽  
Author(s):  
Yujie Li ◽  
Jianru Li ◽  
Yun Li ◽  
Hyoungseop Kim ◽  
Seiichi Serikawa
Keyword(s):  
Image Enhancement ◽  
Deep Sea ◽  
Low Light ◽  
Underwater Image

scholarly journals A Review on Underwater Image Enhancement

2020 ◽  
pp. 27-34
Author(s):  
Mohammad Moiz Ashrafi ◽  
Apurv Verma ◽  
Abhishek Badholia
Keyword(s):  
Image Enhancement ◽  
Deep Water ◽  
Research Area ◽  
Light Variation ◽  
Low Light ◽  
Underwater Image

While capturing underwater image there are lot of imposed due to low light, light variation, poor visibility. Photography is about light, but since water has an a lot more prominent density than air — around 800 times more noteworthy not all wavelengths of light travel similarly well inside it. This implies as we go down into deep water, we lose the shades of the range one by one. This is the reason submerged photographs lose all the red and orange hues even at a genuinely shallow profundity and appear to be increasingly more blue as we go deep in water, henceforth captured image need enhancement. It’s a vital research area, in this paper we will review different techniques of underwater image enhancement.

scholarly journals An Underwater Image Enhancement Method for Different Illumination Conditions Based on Color Tone Correction and Fusion-Based Descattering

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5567 ◽  
Author(s):  
Yidan Liu ◽  
Huiping Xu ◽  
Dinghui Shang ◽  
Chen Li ◽  
Xiangqian Quan
Keyword(s):  
Image Enhancement ◽  
Deep Sea ◽  
Incident Light ◽  
Water Environment ◽  
Color Tone ◽  
Low Contrast ◽  
New Model ◽  
Underwater Image ◽  
Color Shift ◽  
Different Types

In the shallow-water environment, underwater images often present problems like color deviation and low contrast due to light absorption and scattering in the water body, but for deep-sea images, additional problems like uneven brightness and regional color shift can also exist, due to the use of chromatic and inhomogeneous artificial lighting devices. Since the latter situation is rarely studied in the field of underwater image enhancement, we propose a new model to include it in the analysis of underwater image degradation. Based on the theoretical study of the new model, a comprehensive method for enhancing underwater images under different illumination conditions is proposed in this paper. The proposed method is composed of two modules: color-tone correction and fusion-based descattering. In the first module, the regional or full-extent color deviation caused by different types of incident light is corrected via frequency-based color-tone estimation. And in the second module, the residual low contrast and pixel-wise color shift problems are handled by combining the descattering results under the assumption of different states of the image. The proposed method is experimented on laboratory and open-water images of different depths and illumination states. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms many other methods in enhancing the quality of different types of underwater images, and is especially effective in improving the color accuracy and information content in badly-illuminated regions of underwater images with non-uniform illumination, such as deep-sea images.

scholarly journals Image Enhancement using Recursive Standard Intensity Deviation Based Clipped Sub Image Histogram Equalization

2019 ◽  
Vol 9 (2) ◽  
pp. 3933-3937
Keyword(s):  
Image Enhancement ◽  
Histogram Equalization ◽  
Light Conditions ◽  
Low Light ◽  
Image Histogram ◽  
Output Image ◽  
Standard Intensity ◽  
Underwater Image ◽  
Image Inspection ◽  
Low Exposure

The low exposure image enhancement has become indispensable inimage processing for better visibility. The most challenging in image enhancement is especially to curtail overenhancement problems. This paper presents a method, performs the separation of the histogram based on respective standard intensity deviation value and then recursively equalizes all sub histograms independently. The over-enhancement problem is minimized by this method. It applies more in an underwater image, because of its low light conditions. The experiment results are analyzed in terms of entropy and output image inspection. The proposed method results show significant improvement over earlier recursive based histogram equalization algorithms.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

scholarly journals Underwater Image Enhancement Based on Multi-Scale Fusion and Global Stretching of Dual-Model

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Huajun Song ◽  
Rui Wang
Keyword(s):  
Image Enhancement ◽  
Poor Performance ◽  
Weight Coefficient ◽  
Color Contrast ◽  
Dual Model ◽  
Spatial Cues ◽  
Multi Scale ◽  
Imaging Model ◽  
Underwater Image ◽  
Enhancement Method

Aimed at the two problems of color deviation and poor visibility of the underwater image, this paper proposes an underwater image enhancement method based on the multi-scale fusion and global stretching of dual-model (MFGS), which does not rely on the underwater optical imaging model. The proposed method consists of three stages: Compared with other color correction algorithms, white-balancing can effectively eliminate the undesirable color deviation caused by medium attenuation, so it is selected to correct the color deviation in the first stage. Then, aimed at the problem of the poor performance of the saliency weight map in the traditional fusion processing, this paper proposed an updated strategy of saliency weight coefficient combining contrast and spatial cues to achieve high-quality fusion. Finally, by analyzing the characteristics of the results of the above steps, it is found that the brightness and clarity need to be further improved. The global stretching of the full channel in the red, green, blue (RGB) model is applied to enhance the color contrast, and the selective stretching of the L channel in the Commission International Eclairage-Lab (CIE-Lab) model is implemented to achieve a better de-hazing effect. Quantitative and qualitative assessments on the underwater image enhancement benchmark dataset (UIEBD) show that the enhanced images of the proposed approach achieve significant and sufficient improvements in color and visibility.

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