Enhancement of Degraded Images by Natural Phenomena

The efficiency of environmental monitoring through imagery data is strongly dependent on the quality of the acquired information, despite weather conditions or other uncontrolled degradation factor. This article describes a series of combined techniques of image enhancement to partially recover information “lost” due to unfavorable operational conditions or natural phenomena, such as: fog, rainstorms, underwater dust (green dust), poor illumination, etc. We based our approach on a process known as homomorphic filtering, which is intrinsically related to the transformation from the spatial to the frequency domains, directly involving the Fourier Transforms, followed by specific enhancement techniques, such as Clipping and Stretching. Although, the use of these techniques separately, without the proper adaptation and coupling, can result in damaging even more the image, the authors developed an efficient sequence of enhanced filtering able to recover most of the affected information. Moreover, the proposed methodology proved to be generally applicable to a large class of images in poor conditions, with a performance comparable to the methodology