Single Image Dehazing and Edge Preservation Based on the Dark Channel Probability-Weighted Moments
Autor: | Riad Alharbey, Ameen Banjar, Rehan Mehmood Yousaf, Zahid Mehmood, Hafiz Adnan Habib, Omar Aboulola |
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Rok vydání: | 2019 |
Předmět: |
Article Subject
Computer science business.industry lcsh:Mathematics General Mathematics General Engineering 020207 software engineering 02 engineering and technology lcsh:QA1-939 lcsh:TA1-2040 Darkness 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Halo Single image lcsh:Engineering (General). Civil engineering (General) business |
Zdroj: | Mathematical Problems in Engineering, Vol 2019 (2019) |
ISSN: | 1563-5147 1024-123X |
DOI: | 10.1155/2019/9721503 |
Popis: | The method of single image-based dehazing is addressed in the last two decades due to its extreme variating properties in different environments. Different factors make the image dehazing process cumbersome like unbalanced airlight, contrast, and darkness in hazy images. Many estimating and learning-based techniques are used to dehaze the images to overcome the aforementioned problems that suffer from halo artifacts and weak edges. The proposed technique can preserve better edges and illumination and retain the original color of the image. Dark channel prior (DCP) and probability-weighted moments (PWMs) are applied on each channel of an image to suppress the hazy regions and enhance the true edges. PWM is very effective as it suppresses low variations present in images that are affected by the haze. We have proposed a method in this article that performs well as compared to state-of-the-art image dehazing techniques in various conditions which include illumination changes, contrast variation, and preserving edges without producing halo effects within the image. The qualitative and quantitative analysis carried on standard image databases proves its robustness in terms of the standard performance evaluation metrics. |
Databáze: | OpenAIRE |
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