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Fast Single Image Haze Removal Scheme Using Self-Adjusting: Haziness Factor Evaluation

Fast Single Image Haze Removal Scheme Using Self-Adjusting: Haziness Factor Evaluation

Sangita Roy, Sheli Sinha Chaudhuri
Copyright: © 2019 |Volume: 3 |Issue: 1 |Pages: 16
ISSN: 2473-537X|EISSN: 2473-5388|EISBN13: 9781522568742|DOI: 10.4018/IJVAR.2019010103
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MLA

Roy, Sangita, and Sheli Sinha Chaudhuri. "Fast Single Image Haze Removal Scheme Using Self-Adjusting: Haziness Factor Evaluation." IJVAR vol.3, no.1 2019: pp.42-57. http://doi.org/10.4018/IJVAR.2019010103

APA

Roy, S. & Chaudhuri, S. S. (2019). Fast Single Image Haze Removal Scheme Using Self-Adjusting: Haziness Factor Evaluation. International Journal of Virtual and Augmented Reality (IJVAR), 3(1), 42-57. http://doi.org/10.4018/IJVAR.2019010103

Chicago

Roy, Sangita, and Sheli Sinha Chaudhuri. "Fast Single Image Haze Removal Scheme Using Self-Adjusting: Haziness Factor Evaluation," International Journal of Virtual and Augmented Reality (IJVAR) 3, no.1: 42-57. http://doi.org/10.4018/IJVAR.2019010103

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Abstract

At present the classical problem of visibility improvement is hot topic of research. An image formation optical model is presented where a clear day image has high contrast with respect to an image plagued with bad weather. A degraded daytime image has high intensity with minimum deviation among pixels in every channel. No reference digital image haze removal is a problem. The static haziness factor for all types of images cannot be applicable for effective haze removal. A minimum intensity channel of the three RGB channels is estimated as transmission of an image with a dynamic haziness factor to be a ratio of minimum to maximum pixel intensity of the hazy image. Adaptive contrast, extinction coefficient, the maximum visible distance of hazy images as well as dehazed images from each image are evaluated uniquely. The resulting high-quality haze free image with linear computational complexity O(n) is appropriate for real time applications. The effectiveness of the technique is validated by quantitative, and qualitative evaluations.

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