A real-time system for restoration of images degraded by haze is presented. First, a transmission function estimator is automatically constructed using genetic programming. Next, the resultant estimator is employed to compute the transmission function of the scene by processing an input hazy image. Finally, the estimated transmission function and the hazy image are used in a restoration model based on atmospheric optics to obtain a haze-free image. The proposed method is implemented in a laboratory prototype for high-rate image processing. The performance of the proposed approach is evaluated in terms of objective metrics using synthetic and real-world images.

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Jose Enrique Hernandez-Beltran, Victor H. Diaz-Ramirez, and Rigoberto Juarez-Salazar, "Real-time image dehazing using genetic programming," Proc. SPIE 11136, Optics and Photonics for Information Processing XIII, 111360V (Presented at SPIE Optical Engineering + Applications: August 14, 2019; Published: 6 September 2019); https://doi.org/10.1117/12.2528510.