Detection and Classification of Haze Affected Images Using CNN Approach

Abstract

Detection and classifications of the haze affected image is important for the real time multimedia data transmission and reception in remote mode in order to improve the quality of the received image or video sequences. In this paper, Convolutional Neural Networks (CNN) classification approach is used with Shearlet Transform for the detection and segmentation of haze affected images.The image to be tested for haze pattern detection is preprocessed and then it is decomposed with shearlet transform. The features are computed from the shearlet transform decomposed coefficients and then these computed features are classified by the deep learning CNN for identifying the haze affected images. This proposed haze classification method is tested on both indoor and outdoor environmental images.