In this paper, we present a simple yet powerful deep neural network for natural image dehazing. The proposed method is designed based on U-Net architecture and made some design changes to make it better. We first use Group Normalization replace Batch solve the problem of insufficient batch size due hardware limitations. Second, introduce FReLU activation into block, which can achieve capturing ...

Images taken in foggy weather condition often suffer from poor visibility and clarity. Images of the outdoor scene which are captured under bad weather conditions contain atmospheric degradation such as haze, fog, smoke caused by the particles present in the atmosphere resulting in the absorption and scattering of the light, which travels from the scene point of the observer. Due to the presenc...

This paper presents a review on the different haze removal techniques. Haze brings trouble to many computer vision/graphics applications as it diminishes the visibility of the scene. Haze is formed due to the two fundamental phenomena that are attenuation and the air light. Attenuation reduces the contrast and air light increases the whiteness in the scene. Haze removal techniques recover the c...

In this paper, we propose an efficient algorithm to directly restore a clear image from a hazy input. The proposed algorithm hinges on an end-to-end trainable neural network that consists of an encoder and a decoder. The encoder is exploited to capture the context of the derived input images, while the decoder is employed to estimate the contribution of each input to the final dehazed result us...

Currently, most single image dehazing models cannot run an ultra-high-resolution (UHD) with a GPU shader in real-time. To address the problem, we introduce principle of infinite approximation Taylor's theorem Laplace pyramid pattern to build model which is capable handling 4K hazy images The N branch networks network correspond constraint terms theorem. Low-order polynomials reconstruct low-fre...

Since the dark channel prior (DCP)-based dehazing method is ineffective in sky area and will cause problem of too color distortion image, we propose a novel based on segmentation image fusion. We first segment according to characteristics non-sky then estimate atmospheric light transmission map DCP correct them, fuse original after contrast adaptive histogram equalization improve details inform...

Poor weather condition such as fog, rain or haze causes problem in getting information from image. As computer vision system extracts features from the scene, it is important that reliable information could be obtained by removing haze. This paper proposes a fast fog removal method which is implementable in hardware for single image. Using pixel-based median channel of haze image, we can estima...