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 Retinex Color Balanced Piecewise Contrast and Fuzzy Trilateral Filter for Underwater Image Enhancement

2019 ◽  
Vol 8 (4) ◽  
pp. 10815-10822
Keyword(s):  
Image Enhancement ◽  
Piecewise Linear ◽  
Research Area ◽  
Color Correction ◽  
Computational Time ◽  
Color Contrast ◽  
Contrast Model ◽  
White Balance ◽  
Trilateral Filter ◽  
Underwater Image

Over the past few years, underwater observation has become an active research area. Due to the higher rate of image degradation in the underwater environment, image enhancement has become one of the problems to be addressed for the underwater research. Underwater images face limitations like color correction, white balance, color contrast and haze. To overcome those problems, a novel fusion method based on the Retinex Color-balanced Piecewise-contrast and Fuzzy Reinforced Trilateral Filter (RCP-FRTF) method is presented for underwater image improvement. With the underwater image given as input, to start with, a color correction model based on the Retinex multi proportions is presented. With the color corrected output obtained, an Eigen-based White Balancing method is applied to generate color balanced model. With the color balanced underwater image, color contrasting is performed using the Piecewise Linear Color Contrast model. After obtaining the latter, the contrast is said to be improved to a better level. Finally, to generate a haze-free image a Fuzzy Reinforced Trilateral filter is applied. The enhanced and de-hazed images are distinguished by reduced noise level, thus enhanced visibility and contrast while the finest edges are enhanced. The proposed RCP-FRTF method provides better performance in terms of PSNR, computational time, complexity and accuracy as compared to conventional methods.

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.

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

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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