Single image dehazing

Abstract

In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in addition to the transmission function. This allows us to resolve ambiguities in the data by searching for a solution in which the resulting shading and transmission functions are locally statistically uncorrelated. A similar principle is used to estimate the color of the haze. Results demonstrate the new method abilities to remove the haze layer as well as provide a reliable transmission estimate which can be used for additional applications such as image refocusing and novel view synthesis.

Mt. Kelud haze removal using color attenuation prior

“…Among others, Tan [22] observation stated that the haze-free image more contrast than the image containing haze, and be able to maximize the contrast in a local region of the input image. Fattal [23] were able to achieve good results by assuming that the transmission and shadows on the surface locally unrelated. Finally, a very good approximation filed He et al, in which they use dark pixels in the local window dark pixels to produce a rough estimate of the transmission map [24] that obtain results exceeding other algorithms and even managed to dense haze.…”

“…The visual field of computers and computer graphics, mathematical models used to describe the formation of haze is: [14,15,18,21] …”

“…During the last twenty years, haze removal techniques were successfully elaborated [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Initial attempts focused on contrast enhancement of a single image using histogram equalization [8][9][10].…”

“…In terms of haze removal of color images, [18] proposes independent component analysis (ICA), however, it is difficult to deal with dense-haze images. He et al [19] suggest the dark channel prior (DCP) approach for non-sky images based one color channel.…”

Single image haze removal based on two steps

“…4 Fattal removed the haze of the image by estimating the albedo of the radiance image. 5 He et al proposed a haze removal method based on the dark channel prior to restore the radiance image. 6 Li et al proposed a method based on glow and multiple light colors for removing the haze of the night image.…”