APPLICATION OF MACHINE LEARNING BASED RANDOM FOREST REGRESSOR IN IMAGE DEHAZING

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Published: Feb 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i1.5312
Keywords:
Machine learning, Dehazing, Random forest Regressor, Haze Removal Algorithms

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Tabrej Khan
Department of Information Sciences, Faculty of Computing and Information Technology Rabigh (FCITR) King Abdulaziz University, Jeddah, Saudi Arabia
Syed Asif Hassan
Department of Computer Science, Faculty of Computing and Information Technology Rabigh (FCITR) King Abdulaziz University, Jeddah, Saudi Arabia

Abstract

Low visibility causes haze in images due to fog or dust particles in the atmosphere. The haze causes color distortion and even blurring in the images captured. Machine learning approach has been considered to provide optimized haze removal results to generate higher quality images from where information can be extracted. In this context, machine learning-based random forest regressor algorithm along with post-processing techniques was proposed as a superior solution for de-hazing images and thereby generating higher quality images in comparison to other direct de-hazing methods.

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Vol. 9 No. 1 (2018): January-February 2018
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