Adversary imaging condition such as in a hazy weather is a challenge in the community of image processing. To address the challenge of haze removal, several model-based approaches have been reported recently. Among them, a single image haze removal scheme based on dark channel prior (DCP) was presented in [1] and has been getting popular because of its satisfactory performance for most of cases...

Haze removal has been a very challenging problem due to its ill-posedness, which is more ill-posed if the input data is only a single hazy image. In this paper, we present a new approach for removing haze from a single input image. The proposed method combines the model widely used to describe the formation of a haze image with the assumption in Retinex that an image is the product of the illum...

In this paper a novel method for removing haze is given which is based on the Hue Saturation Value color model together with dark channel subtraction. Single image fog/haze removal is a challenging task due to its ill posed nature. As fog/haze increases the brightness of the images captured also increases. In the current wok, a new methodology has been used which involves the subtraction of ext...

Fog phenomena bring about air flow gentle generating and also decline this awareness involving made from photograph caught in the camera. To increase awareness, air flow gentle evaluation is essential regarding photograph errors removal. As air flow gentle can be quite dazzling, this conventional methods immediately select dazzling p regarding air flow gentle estimation.In this paper improved/h...

Images of outdoor scenes are usually degraded under bad weather conditions, which results in a hazy image. To date, most haze removal methods based on a single image have ignored the effects of sensor blur and noise. Therefore, in this paper, a three-stage algorithm for haze removal, considering sensor blur and noise, is proposed. In the first stage, we preprocess the degraded image and elimina...

Single image haze removal, which is to recover the clear version of a hazy image, challenging task in computer vision. In this paper, an additive model proposed approximate formation process. contrast with traditional optical model, it regards as layer clean image. The thus avoids estimating medium transmission rate and global atmospherical light. addition, based on critical observation that ch...