Clear and wide-angle images are essential to detect and trace objects for applications such as CCTV and unmanned vehicles. Fog, haze, and rain causes problem in getting clear image and lowers the detection rate of objects. To remove haze, we use median dark channel prior which can reduce the complexity of hardware. Image stitching stitches a number of images from multiple cameras into single wi...

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...

Poor visibility in bad weather, such as haze and fog, is a major problem for many applications of computer vision. Thus, haze removal is highly required for receiving high performance of the vision algorithm. In this paper, we propose a new fast dehazing method for real-time image and video processing. The transmission map estimated by an improved guided filtering scheme is smooth and respect w...

This paper has proposed a new fog removal technique IDCP which will integrate dark channel prior with CLAHE and adaptive gamma correction to remove the fog from digital images. Fog in image reduces the visibility of the digital images. Poor visibility not only degrades the perceptual image quality but it also affects the performance of computer vision algorithms such as object detection, tracki...

In order to improve the traffic visibility in haze weathers, a Retinex algorithm based on the changing scale for haze removal with a depth map is proposed. It requires the haze image dark channel prior treatment to obtain the estimated depth map. Then it is according to the depth map to calculate Retinex scales for different parts of a hazy image. Finally a single scale Retinex transform is per...

A novel and effective approach is proposed in this paper to detect smoke using transmission from image or video frame. Inspired by the airlightalbedo ambiguity model, we introduce the concept of transmission as a new essential feature of smoke, which is employed to detect the smoke and also determine its corresponding thickness distribution. First, we define an optical model for smoke based on ...

Most of the computer applications use digital images. Digital image processing acts an important role in the analysis and interpretation of data, which is in the digital form. Images and videos of outdoor scenes are mainly affected by the bad weather conditions such as haze, fog, mist etc. It will result in poor visibility of the scene caused by the lack of quality. It will make awful impact on...

Bad weather conditions such as fog, haze, and dust often reduce the performance of outdoor cameras. To improve the effectiveness of surveillance and in-vehicle cameras under such conditions, we propose a method based on a dark channel prior for quickly defogging images. It first estimates the intensity of the atmospheric light by searching the sky area in the foggy image. Then it estimates the ...

There are some deficiencies in the traditional daytime visibility calculation method using CCD digital camera: visibility observation value is accurate while using the artificial objects, but expensive; nonzero internal reflection coefficient of the target lead to inaccurate visibility observation results when using natural objects as the target. A new daytime visibility algorithm based on colo...

This paper has proposed a new fog removal technique IDCP which will integrate dark channel prior with CLAHE and adaptive gamma correction to remove the fog from digital images. Fog in image reduces the visibility of the digital images. Poor visibility not only degrades the perceptual image quality but it also affects the performance of computer vision algorithms such as object detection, tracki...