scholarly journals A Fusion Based Visibility Enhancement of Single Underwater Hazy Image

2018 ◽  
Vol 7 (1) ◽  
pp. 38
Author(s):  
Samarth Borkar ◽  
Sanjiv V. Bonde
Keyword(s):  
Color Space ◽  
Color Constancy ◽  
Discrete Wavelet ◽  
Image Dehazing ◽  
Hsv Color Space ◽  
Underwater Image ◽  
Color Cast ◽  
Value Decomposition ◽  
Visibility Enhancement ◽  
Fusion Scheme

<span lang="EN-IN">Underwater images are prone to contrast loss, limited visibility, and undesirable color cast. For underwater computer vision and pattern recognition algorithms, these images need to be pre-processed. We have addressed a novel solution to this problem by proposing fully automated underwater image dehazing using multimodal DWT fusion. Inputs for the combinational image fusion scheme are derived from Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) for contrast enhancement in HSV color space and color constancy using Shades of Gray algorithm respectively. To appraise the work conducted, the visual and quantitative analysis is performed. The restored images demonstrate improved contrast and effective enhancement in overall image quality and visibility. The proposed algorithm performs on par with the recent underwater dehazing techniques.</span>

scholarly journals Robust Chromatic Adaptation Based Color Correction Technology for Underwater Images

2020 ◽  
Vol 10 (18) ◽  
pp. 6392
Author(s):  
Xieliu Yang ◽  
Chenyu Yin ◽  
Ziyu Zhang ◽  
Yupeng Li ◽  
Wenfeng Liang ◽  
...  
Keyword(s):  
Color Space ◽  
Color Correction ◽  
Test Methods ◽  
Chromatic Adaptation ◽  
Water Type ◽  
Underwater Image ◽  
Other Information ◽  
Color Restoration ◽  
Color Cast ◽  
Imaging Conditions

Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes.

Enhancement of Nonuniformly Illuminated Underwater Images

2020 ◽  
pp. 2154008
Author(s):  
Monika Mathur ◽  
Nidhi Goel
Keyword(s):  
Image Quality ◽  
Color Image ◽  
Light Attenuation ◽  
Color Space ◽  
Discrete Wavelet ◽  
Underwater Image ◽  
Image Capturing ◽  
Contrast Stretching ◽  
Result Analysis ◽  
Image Details

Underwater image capturing is a challenging task due to attenuation of light in water. Scattering and absorption are the results of light attenuation which lead to faded colors and reduced contrast of images, respectively. To deal with these issues and to provide better visual quality image, various enhancement methods have been proposed. This paper proposes the Dual Domain-based Underwater Image Enhancement (DDUIE) method. DDUIE method provides contrast stretching in approximation band of discrete wavelet transformed image followed by intensity adjustment of different color channels in spatial domain. To further improve the color quality, the image is processed in HSV (Hue–Saturation–Value) color space. Result analysis indicates better results for DDUIE method over state-of-the-art methods. Subjective results of DDUIE method show minimization of the bluish-green effect and reduction of nonuniform illumination up to a certain extent. These lead to enhanced color and image details. Quantitative results show that the Underwater Image Quality Measure (UIQM) and Underwater Color Image Quality Evaluation (UCIQE) values between 1 and 2 and between 0 and 1 have been achieved, respectively, which significantly illustrate that images have been enhanced efficiently and also entropy values between 7 and 8 depict the effectiveness of the proposed method in terms of image details.

scholarly journals Singular Value Decomposition Based Features for Automatic Tumor Detection in Wireless Capsule Endoscopy Images

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Vahid Faghih Dinevari ◽  
Ghader Karimian Khosroshahi ◽  
Mina Zolfy Lighvan
Keyword(s):  
Singular Value Decomposition ◽  
Capsule Endoscopy ◽  
Color Space ◽  
Wireless Capsule Endoscopy ◽  
Singular Value ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Data Set ◽  
Value Decomposition ◽  
Wireless Capsule

Wireless capsule endoscopy (WCE) is a new noninvasive instrument which allows direct observation of the gastrointestinal tract to diagnose its relative diseases. Because of the large number of images obtained from the capsule endoscopy per patient, doctors need too much time to investigate all of them. So, it would be worthwhile to design a system for detecting diseases automatically. In this paper, a new method is presented for automatic detection of tumors in the WCE images. This method will utilize the advantages of the discrete wavelet transform (DWT) and singular value decomposition (SVD) algorithms to extract features from different color channels of the WCE images. Therefore, the extracted features are invariant to rotation and can describe multiresolution characteristics of the WCE images. In order to classify the WCE images, the support vector machine (SVM) method is applied to a data set which includes 400 normal and 400 tumor WCE images. The experimental results show proper performance of the proposed algorithm for detection and isolation of the tumor images which, in the best way, shows 94%, 93%, and 93.5% of sensitivity, specificity, and accuracy in the RGB color space, respectively.

scholarly journals Comparative Analysis of Color Image Watermarking Technique in RGB, YUV, and YCbCr Color Channels

2015 ◽  
Vol 15 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Roshan Koju ◽  
Shashidhar Ram Joshi
Keyword(s):  
Color Image ◽  
Image Watermarking ◽  
Color Space ◽  
Discrete Wavelet ◽  
Color Image Watermarking ◽  
Comparative Performance ◽  
Ycbcr Color Space ◽  
Rgb Color Space ◽  
Value Decomposition ◽  
Color Channels

Since there are a number of color spaces, it has always been a big question to choose one for watermarking. The aim of this work is to find out better color space, among the frequently used one, under the same condition. Comparative performance analysis of color image watermarking technique in color channels of RGB, YUV, YCbCrcolor spaces was studied. For this purpose, color channels were watermarked using single level discrete wavelet transform-singular value decomposition (DWT-SVD). PSNR, and SSIM were used to test the imperceptibility of watermarked images. PSNR and NCC were used to measure the similarity of extracted and original watermarks.The maximum recorded PSNR value is 62.372 for R channel of RGB color space with SSIM value equal to 0.9709. Color channels of YCbCr color space were observed to be more robust and transparent as watermark image is best recovered from YCbCr color space with NCC values in the range 0.86 to 0.877 and SSIM values in the range 0.546to 0.554 under various geometric attacks.DOI: http://dx.doi.org/njst.v15i2.12130Nepal Journal of Science and Technology Vol. 15, No.2 (2014) 133-140

Traffic Image Dehazing Based on HSV Color Space

2021 ◽  
Author(s):  
Can Ding ◽  
Zhe Zhang ◽  
Fan Li ◽  
Jing Zhang
Keyword(s):  
Color Space ◽  
Image Dehazing ◽  
Hsv Color Space

An HVS Inspired Robust Non-blind Watermarking Scheme in YCbCr Color Space

2018 ◽  
Vol 18 (03) ◽  
pp. 1850015 ◽  
Author(s):  
Aniket Roy ◽  
Arpan Kumar Maiti ◽  
Kuntal Ghosh
Keyword(s):  
Image Watermarking ◽  
Color Space ◽  
Singular Value ◽  
Strength Parameter ◽  
Perceptual Quality ◽  
Discrete Wavelet ◽  
Blind Watermarking ◽  
Ycbcr Color Space ◽  
Value Decomposition ◽  
Watermarking Scheme

Digital Watermarking is an important tool for copyright protection. A good quality watermarking scheme should provide both perceptual transparency as well as robustness against attacks. Many efficient schemes exist for grayscale image watermarking, but relatively less attention has been paid to watermarking for color images. Moreover, the existing works do not provide adequate justification for the possible choice of color space. In this paper, justification is provided for the choice of YCbCr color space for watermark embedding. A human visual system (HVS)-inspired image-adaptive non-blind watermarking scheme in the YCbCr space has subsequently been proposed. This new algorithm has been referred to as the Additive Embedding Scheme (AES). It comprises of a modified watermarking strength parameter ([Formula: see text]), in combination with the discrete wavelet transform and singular value decomposition (DWT-SVD). Experimental results demonstrate that the proposed watermarking scheme in YCbCr color space provides better perceptual quality as well as robustness against attacks as compared to existing schemes. We have further improvised the aforementioned scheme to come up with a Multiplicative Embedding Scheme (MES) for additional robustness against a special type of attack, viz. the Singular Value Exchange Attack.

scholarly journals Enhancing the Tablet Images using Noise Reduction Algorithms by Analyzing Different Color Models

2019 ◽  
Vol 9 (2) ◽  
pp. 148-155
Keyword(s):  
Healthcare Professionals ◽  
Wavelet Packet ◽  
Color Space ◽  
Packet Transmission ◽  
Maximum Efficiency ◽  
Identification System ◽  
Discrete Wavelet ◽  
Hsv Color Space ◽  
Space Model ◽  
Different Color

Unidentified tablets are challenges to both patients and healthcare professionals. Using these unknown tablets results in undesirable reaction of drug and also it is foundation to ill health that leads to death even sometimes. Thus, recognition of unidentified tablets is a significant task in medical industry. Identification of tablets is one of the major concerns for public and pharmacists, which can be carried out by means of either text-based or image-based methods. The tablet identification system is focused on removing noise from the tablet images using algorithms like Independent Component Analysis (ICA) and Discrete Wavelet Packet Transmission (DWPT). The three color space models, i.e., RGB (Red-Green-Blue), YCbCr (Y-Luma, CChroma of blue and red components) and HSV (Hue-SaturationValue) are examined for their efficiency on removing noise from tablets. For each color space model, the two denoising algorithms, ICA and DWPT are analyzed and applied. The result is interpreted using metrics like PSNR, FoM, MSSI and Speed. Experimental results proved that denoising with HSV color space model gives maximum efficiency when used with ICA and DWPT-based tablet identification systems.

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