Real time polarimetric dehazing

Abstract

Remote sensing is a rich topic due to its utility in gathering detailed accurate information from locations that are not economically feasible traveling destinations or are physically inaccessible. However, poor visibility over long path lengths is problematic for a variety of reasons. Haze induced by light scatter is one cause for poor visibility and is the focus of this article. Image haze comes about as a result of light scattering off particles and into the imaging path causing a haziness to appear on the image. Image processing using polarimetric information of light scatter can be used to mitigate image haze. An imaging polarimeter which provides the Stokes values in real time combined with a "dehazing" algorithm can automate image haze removal for instant applications. Example uses are to improve visual display providing on-the-spot detection or imbedding in an active control loop to improve viewing and tracking while on a moving platform. In addition, removing haze in this manner allows the trade space for a system operational waveband to be opened up to bands which are object matched and not necessarily restricted by scatter effects.

Generalized Polarimetric Dehazing Method Based on Low-Pass Filtering in Frequency Domain

“…As a result, the DoP of the scattering light usually cannot be estimated accurately, and the quality of the dehazed images is unstable accordingly. 2 of 12 To overcome this problem, the DoP of the scattering light is usually tuned by a bias parameter to improve the quality of the dehazed image [5,12,18]. However, this bias parameter is affected by the camera itself and is related to different scattering media, so it is not a fixed value and must be tuned manually in the dehazing process.…”

An image dehazing method based on scene segmentation

“…It only improves the image quality to satisfy our need by enhancing the contrast of the images and highlighting the image detail, such as histogram equalization[1], retinex theory [2],and so on. The other dehazing algorithm is based on image recovery [3][4][5][6][7][8][9][10][11]. This kind of algorithm is based on the physical model of atmosphere scattering.…”

Dehazing method through polarimetric imaging and multi-scale analysis

“…J.P.Tarel designs an effective filtering function by which the strength of the atmospheric veil can be inferred directly [5]. Given polarization effect when image in haze weather, polarimetric imaging has proved to be a useful method for effectively improving the visibility of the image [6][7][8][9][10]. Schechner et al demonstrated that one can enhance the quality of images taken in poor visibility weather by two or more images taken with different degrees of polarization.…”