Real-time haze removal in monocular images using locally adaptive processing


This research presents the design of a real-time system to remove the effects of haze in a sequence of monocular images. The system firstly estimates the medium transmission function from an observed hazy image using locally adaptive neighborhoods and calculation of order statistics. Next, the haze-free image is retrieved using the estimated transmission function and a physics-based restoration model. The performance of the proposed system is evaluated and compared with that of similar existing techniques in terms of objective metrics. The obtained results exhibit that the proposed system yields a higher performance in comparison with tested similar methods. Because of its high computational efficiency, the proposed system is able to operate at high rate and it is suitable for real-time applications.

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This research was supported by Secretaría de Investigación y Posgrado - Instituto Politécnico Nacional, project SIP20171387 and Consejo Nacional de Ciencia y Tecnología, project Catedras-CONACYT-880.

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Correspondence to Victor H. Diaz-Ramirez.

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Diaz-Ramirez, V.H., Hernández-Beltrán, J.E. & Juarez-Salazar, R. Real-time haze removal in monocular images using locally adaptive processing. J Real-Time Image Proc 16, 1959–1973 (2019).

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  • Image dehazing
  • Real-time image processing
  • Locally adaptive neighborhoods
  • Parallel processing
  • Graphics processing unit