This paper proposes an improved dark channel prior for removing haze from images. Dark channel prior is an effective method for removing haze. Dark channel is an image in the same size as the hazy image which is obtained by dividing the RGB images into windows and for each window, the minimum of each R, G and B channels are calculated. Then again the minimum of these three values is calculated ...

The dark channel prior (DCP) technique is an effective method to enhance hazy images. Dark channel is an image with the same size as the hazy image which represents the haze severity in different places of the image. The DCP method suffers from two problems: it is incapable for removing haze from smooth regions, causing blocking effects on these areas; it cannot properly reduce a haze with a no...

The sky regions of foggy image processed by all the existing conventional dehazing methods are degraded by color distortion and severe noise. This paper proposes an improved algorithm which combines dark channel prior and inverse image. We first invert the foggy image, and then estimate the transmission of the inverse image. At last, compared with the non-inversed transmission, the larger value...

Single-image dehazing plays a significant preprocessing role in machine vision tasks. As the dark-channel-prior method will fail sky region of image, resulting inaccurately estimated parameters, and given failure many methods to address large band haze, we propose simple yet effective for single-image based on an improved bright prior dark channel prior. First, use Otsu by particle swarm optimi...

For traditional dark channel prior (DCP) imaging through haze environments, intensity information acts as the carrier to acquire reflective character of dehazed target image. We introduce polarization auxiliary into DCP process for achieving better performance that can improve detection or tracking. In this paper, a system with split-amplitude structure is designed enable real-time acquisition ...

The reflectance of inhomogeneous objects can be described as a linear combination of diffuse and specular reflection components. Most computer vision algorithms assume that visually observable surfaces consist only of diffuse reflection. The existence of specular reflection can be misleading to these computer vision algorithms. A new algorithm dark channel prior based specularity removal is pro...