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Underwater Image Enhancement Using Customized CLAHE and Adaptive Color Correction
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作者 Mousa Alhajlah 《Computers, Materials & Continua》 SCIE EI 2023年第3期5157-5172,共16页
Underwater images degraded due to low contrast and visibility issues.Therefore,it is important to enhance the images and videos taken in the underwater environment before processing.Enhancement is a way to improve or ... Underwater images degraded due to low contrast and visibility issues.Therefore,it is important to enhance the images and videos taken in the underwater environment before processing.Enhancement is a way to improve or increase image quality and to improve the contrast of degraded images.The original image or video which is captured through image processing devices needs to improve as there are various issues such as less light available,low resolution,and blurriness in underwater images caused by the normal camera.Various researchers have proposed different solutions to overcome these problems.Dark channel prior(DCP)is one of the most used techniques which produced a better Peak Signal to Noise Ratio(PSNR)value.However,DCP has some issues such as it tends to darken images,reduce contrast,and produce halo effects.The proposed method solves these issues with the help of contrast-limited adaptive histogram equalization(CLAHE)and the Adaptive Color Correction Method.The proposed method was assessed using Japan Agency for Marine-Earth Science and Technology(JAMSTEC),and some images were collected from the internet.The measure of entropy(MOE),Measure of Enhancement(EME),Mean Square Error(MSE),and PSNR opted as performance measures during experiments.The values of MSE and PSNR achieved by the proposed framework are 0.26 and 32 respectively which shows better results. 展开更多
关键词 ENHANCEMENT color diminishing CONTRAST fusion technique color balancing technique CLAHE dark channel prior
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Fast Single Image Haze Removal Method for Inhomogeneous Environment Using Variable Scattering Coefficient
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作者 Rashmi Gupta Manju Khari +4 位作者 Vipul Gupta Elena Verdú Xing Wu Enrique Herrera-Viedma Rubén González Crespo 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第6期1175-1192,共18页
The images capture in a bad environment usually loses its fidelity and contrast.As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the ... The images capture in a bad environment usually loses its fidelity and contrast.As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the environment,therefore the energy gets lost due to multiple scattering till it arrives its destination,and this degrades the images.So the images taken in bad weather appear in bad quality.Therefore,single image haze removal is quite a bit tough task.Significant research has been done in the haze removal algorithm but in all the techniques,the coefficient of scattering is taken as a constant according to the homogeneous atmosphere but in real time this does not happen.Therefore,this paper introduces a simple and efficient method so that the scattering coefficient becomes variable according to the inhomogeneous environment.Then,this research aims to remove the haze with the help of a fast and effective algorithm i.e.,Prior Color Fading,according to the inhomogeneous environmental properties.Thereby,to filter the depth map,the authors used a weighted guided image filtering which removes the drawbacks of guided image filter.Afterwards the scattering coefficient is made variable according to the inhomogeneous atmosphere and then the Simple Color Balance Algorithm is applied so that the readability property of images can be increased.The proposed method tested on various general outdoor images and synthetic hazy images and analyzed on various parameters Mean Square Error(MSE),Root Mean Square Error(RMSE),Peak Signal to Noise Ratio(PSNR),Mean Structural Similarity(MSSIM)and the Universal Objective Quality Index(UQI).Experimental results for the proposed method show that the proposed approach provides better results as compared to the state-of-the-art haze removal algorithms. 展开更多
关键词 Image dehazing scattering coefficient simple color balance inhomogeneous environment
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