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Low Complexity Single Color Image Dehazing Technique

Low Complexity Single Color Image Dehazing Technique

SANGITA ROY, Sheli Sinha Chaudhuri
Copyright: © 2018 |Pages: 14
ISBN13: 9781522552468|ISBN10: 1522552464|EISBN13: 9781522552475
DOI: 10.4018/978-1-5225-5246-8.ch004
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MLA

ROY, SANGITA, and Sheli Sinha Chaudhuri. "Low Complexity Single Color Image Dehazing Technique." Intelligent Multidimensional Data and Image Processing, edited by Sourav De, et al., IGI Global, 2018, pp. 116-129. https://doi.org/10.4018/978-1-5225-5246-8.ch004

APA

ROY, S. & Chaudhuri, S. S. (2018). Low Complexity Single Color Image Dehazing Technique. In S. De, S. Bhattacharyya, & P. Dutta (Eds.), Intelligent Multidimensional Data and Image Processing (pp. 116-129). IGI Global. https://doi.org/10.4018/978-1-5225-5246-8.ch004

Chicago

ROY, SANGITA, and Sheli Sinha Chaudhuri. "Low Complexity Single Color Image Dehazing Technique." In Intelligent Multidimensional Data and Image Processing, edited by Sourav De, Siddhartha Bhattacharyya, and Paramartha Dutta, 116-129. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5246-8.ch004

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Abstract

Atmospheric particulate matter (APM) disturbs the biotic environment creating global warming, health hazards, and last but not the least, visibility reduction. Removing haze from degraded image is an extremely ill-posed inverse problem. Real time is another factor influencing the quality of resulting image. There is a trade-off between time and quality of resulting image. Single image makes the algorithms more challenging. In this work, the authors have developed fast, efficient, single gray or color image visibility improvement algorithms based on image formation optical model with minimum order statistics filter (MOSF) as the transmission model. The quantitative and qualitative evaluations of the proposed algorithms have been studied with other existing algorithms. The result shows improvements over existing state-of-the art algorithms with minimum time. Time has been evaluated by execution time along with time complexity Big (O). The resultant images are visibly clear satisfying the criteria for computer vision applications.

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