GAN based image deblurring using dark channel prior

Blind Image Deblurring Using Dark Channel Prior Supplemental Material

Overview In this supplemental material, we provide the proofs of Property 1 and Property 2 in Sections 1 and 2 respectively. We analyze the properties of the dark channel prior in image deblurring and demonstrate its effectiveness on natural images, text images and low-illumination images in Section 3. Section 4 provides detailed analysis of the proposed algorithm The algorithm details for solv...

Adaptive Image Dehazing via Improving Dark Channel Prior

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...

Single Image Dehazing Algorithm Based on Dark Channel Prior and Inverse Image

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...

Improving Dark Channel Prior for Single Image Dehazing

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 ...

Blind image deblurring using elastic-net based rank prior