The images acquired in haze conditions are significantly degraded due to the presence of atmospheric particles. These have low contrast, poor visibility, and some information is lost as well. characteristics severely hinder further processing applications which being used. polarimetric dehazing methods effective for direct imaging enhancing quality. In addition, capability cope with other turbi...

Presence of haze in images obscures underlying information, which is undesirable applications requiring accurate environment information. To recover such an image, a dehazing algorithm should localize and affected regions while ensuring consistency between recovered its neighboring regions. However owing to fixed receptive field convolutional kernels non uniform distribution, assuring difficult...

Many real-world situations such as bad weather may result in hazy environments. Images captured these conditions will have low image quality due to microparticles the air. The light scatter and absorb, resulting images with various effects. In recent years, dehazing has been researched depth handle conditions. Various methods were developed, from traditional deep learning methods. Traditional f...

Image dehazing is one of the problems that need to be solved urgently in field computer vision. In recent years, more and algorithms have been applied image achieved good results. However, after still has color distortion, contrast saturation disorder, other challenges; order solve these problems, this paper, an effective method proposed, which based on improved channel transfer multiexposure f...

Convolutional Neural Network (CNN) recognition rates drop in the presence of noise. We demonstrate a novel method of counteracting this drop in recognition rate by adjusting the biases of the neurons in the convolutional layers according to the noise conditions encountered at runtime. We compare our technique to training one network for all possible noise levels, dehazing via preprocessing a si...

In this paper, we introduce a simple but effective method in order to remove haze in foggy images. We name it as dark pixel detection. Dark pixel is the pixel in haze-free images with values in all of the RGB colour channels close to zero. With this method, we can effectively estimate the thickness of the haze and recover a vivid haze-free scene even when the scene object is inherently similar ...