An Efficient Algorithm for Image Haze Removal in Outdoor Environment

Abstract

Computer vision applications in outdoor environment are mainly affected by factors such as pollution, clouds, shadow, haze, fog. Herein, an algorithm for real-time haze detection and removal in image has been implemented. For this purpose, the Dark Channel Prior technique is used which is efficient method for haze removal and also contains information about the level of haze in the image. Initially, visibility index of image frame is estimated to determine whether image is hazy or not using haze detection model. Thereafter, hazy images are processed with haze removal model to enhance the image visibility. The haze removal model uses guided filter to accelerate the process. Non-hazy images do not require to process with haze removal model. The algorithm has been tested for four datasets, i.e., non-hazy, slightly hazy, medium hazy, and heavily hazy. The proposed algorithm is performing well and also able to tackle the halo effects at some extent.