Haze Identification and Classification Model for Haze Removal Techniques

Abstract

In the modern age, several applications depend on the information collected from the images and its classification. However, due to the poor climatic conditions, the images captured by the camera are degraded in terms of contrast, brightness, color, and sharpness, which create hazy images. Therefore, several techniques have been suggested in the literature to restore the degraded image. Besides, poor climate conditions are not same all the time which leads the idea, that, if images are identified before applying haze removal technique, then it can save processing time which otherwise will be consumed for clear images as well. Therefore, in this article, the haze identification model is proposed to identify the hazy and non-hazy images which makes all haze removal systems more efficient. Moreover, proposed model also classifies the hazy images based on their densities which can be utilized for selection of configuration parameters of haze removal techniques. Finally, the performance of the proposed model is demonstrated and the valuable identification, as well as classification parameters, are computed and presented.