scholarly journals Hazy Underwater Image Enhancement Based on Contrast and Color Improvement Using Fusion Technique

2017 ◽  
Vol 22 (3) ◽  
pp. 31-38
Author(s):  
Ritu Singh ◽  
Mantosh Biswas
Keyword(s):  
Image Enhancement ◽  
Fusion Technique ◽  
White Balance ◽  
Enhancement Technique ◽  
Underwater Image ◽  
Absorption Of Light ◽  
Contrast Stretching ◽  
Degraded Images

Abstract Scattering and absorption of light in water leads to degradation of images captured under the water. This degradation includes diminished colors, low brightness and undistinguishable objects in the image. To improve the quality of such degraded images, we have proposed fusion based underwater image enhancement technique that focuses on improving of the contrast and color of underwater images using contrast stretching and Auto White Balance. Our proposed method is very simple and straightforward that contributes greatly in uplifting the visibility of underwater images.

scholarly journals Comparative study of image enhancement techniques using histogram equalization on degraded images

2018 ◽  
Vol 7 (2.8) ◽  
pp. 468 ◽  
Author(s):  
Shalika Arora ◽  
Megha Agarwal ◽  
Veepin Kumar ◽  
Divya Gupta
Keyword(s):  
Image Processing ◽  
Comparative Study ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Histogram Equalization ◽  
Vital Role ◽  
Enhancement Technique ◽  
Degraded Images

Image Enhancement technique plays a vital role in digital image processing for making an image to be useful for various applications. This technique is used to improve the quality of degraded images.Usually, the degradation is not evenly spread throughout the image, but most of the time it varies from region to region. Our aim is to first identify the region where enhancement is required and improve that region without disturbing its neighbourhood which does not require any improvement. 

PERBANDINGAN METODE HOMOMORPHIC FILTERING DAN METODE CONTRAST STRECHING UNTUK PERBAIKAN KUALITAS CITRA UNDERWATER

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Adi Mora Lubis ◽  
Nelly Astuti Hasibuan ◽  
Imam Saputra
Keyword(s):  
Digital Image ◽  
Water Environment ◽  
Repair Process ◽  
Image Process ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Underwater Image ◽  
Homomorphic Filtering ◽  
Contrast Stretching

Digital imagery is a two-dimensional image process through a digital computer that is used to manipulate and modify images in various ways. Photos are examples of two-dimensional images that can be processed easily. Each photo in the form of a digital image can be processed through a specific software. In the water environment, the light factor greatly influences the results of the quality of the image obtained. With the deepening of underwater shooting, the results obtained will be the darker the quality of the underwater image. . uneven lighting and bluish tones. One of the factors that influence the recognition results in pattern recognition is the quality of the image that is inputted. The image acquired from the source does not always have good quality. The process of repairing digital images that experience interference in lighting. The lighting repair process uses homomorphic filtering and uses contrast striching and will compare the quality of both methods and test to prove the results of image quality between homomorphic filtering and contrast streching. Until later the results of both methods can be seen which is better. homomorphic filtering and contrast stretching can produce image improvements with pretty good performance.Keywords: Digital Image, Underwater Image, Homomorphic Filtering, Contrast Streching, Matlab R2010a

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 An approach for underwater image enhancement based on color correction and dehazing

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142096164
Author(s):  
Yue Zhang ◽  
Fuchun Yang ◽  
Weikai He
Keyword(s):  
Image Enhancement ◽  
Signal To Noise Ratio ◽  
Color Correction ◽  
Superior Performance ◽  
Local Contrast ◽  
Low Contrast ◽  
White Balance ◽  
Average Value ◽  
Underwater Image ◽  
Dark Channel

Due to the absorption and scattering effect on light when traveling in water, underwater images exhibit serious weakening such as color deviation, low contrast, and blurry details. Traditional algorithms have certain limitations in the case of these images with varying degrees of fuzziness and color deviation. To address these problems, a new approach for single underwater image enhancement based on fusion technology was proposed in this article. First, the original image is preprocessed by the white balance algorithm and dark channel prior dehazing technologies, respectively; then two input images were obtained by color correction and contrast enhancement; and finally, the enhanced image was obtained by utilizing the multiscale fusion strategy which is based on the weighted maps constructed by combining the features of global contrast, local contrast, saliency, and exposedness. Qualitative results revealed that the proposed approach significantly removed haze, corrected color deviation, and preserved image naturalness. For quantitative results, the test with 400 underwater images showed that the proposed approach produced a lower average value of mean square error and a higher average value of peak signal-to-noise ratio than the compared method. Moreover, the enhanced results obtain the highest average value in terms of underwater image quality measures among the comparable methods, illustrating that our approach achieves superior performance on different levels of distorted and hazy images.

scholarly journals Deep Learning Approach for Submerged Image Enhancement

2021 ◽  
Vol 9 (10) ◽  
pp. 214-219
Author(s):  
Dr. Geeta Hanji
Keyword(s):  
Deep Learning ◽  
Image Enhancement ◽  
Light Attenuation ◽  
Histogram Equalization ◽  
Color Contrast ◽  
Learning Approach ◽  
Gamma Correction ◽  
Ocean Engineering ◽  
White Balance ◽  
Underwater Image

Abstract: Because of underwater pictures application in ocean engineering, ocean research, marine biology, and marine archaeology to name a few, underwater picture enhancement was widely publicized in the last several years. Underwater photos frequently upshot in low contrast, blurred, color distortion, hazy, poor visible images. This is because of light attenuation, absorption, scattering (forward scattering and backward scattering), turbidity, floating particles. As a result, effective underwater picture solution must be developedin order to improve visibility, contrast, and color qualities for greater visual quality and optical attractiveness. Many underwater picture enhancing approaches have been proposed to overcome these challenges; however they all failed to produce accurate results. Hence for this we first undertook a large scale underwater image dataset which is trained by convolution neural network (CNN) and then we have studied and implemented a deep learning approach called very deep super resolution (VDSR) model for improving the color, contrast, and brightness of underwater photos by using different algorithms such as white balance, histogram equalization, and gamma correction respectively. Moreover, our method is compared with the existing method which reveals that our method surpassesthe existing methods Keywords: CNN, gamma correction, histogram equalization, underwater image enhancement, VDSR, white balance

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.

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