IDSCAN:Image Dehazing Using Spatial and Channel Aware Network

Abstract

Dehazing refers to a method that aims to remove the interference of haze in the image to obtain a high-quality image by some certain ways such as statistical knowledge, image restoration knowledge and deep learning knowledge. Some classical methods have been proposed for removing the haze and achieved some most pleasant performance. However, there is some aliasing phenomena in dehazing results. To address this issue, we propose an effective image dehazing using spatial and channel aware network(IDSCAN) to learn some features with strong representation ability from the images with free-haze. For spatial aware, we extract them by combining some convolutional information with some simple operations such as unfold and reshape. For channel aware, we compute the weight of each channel by the compression in the frequency domain which is implemented by the discrete cosine transform block network (DCTB). Extensive experimental results on the RESIDE haze dataset show that our method outperforms other state-of-art dehazing methods in terms of qualitative and quantitative methods. Simultaneously, we also effective improve the aliasing phenomena of images removed the haze.