Paper ID | TEC-7.8 | ||
Paper Title | BENCHMARKING OF NATURAL SCENE IMAGE DATASET IN DEGRADED CONDITIONS FOR VISIBILITY ENHANCEMENT | ||
Authors | Sourav Dey Roy, Tripura University (A Central University), India; Tannistha Pal, National Institute of Technology Agartala, India; Mrinal Kanti Bhowmik, Tripura University (A Central University), India | ||
Session | TEC-7: Interpolation, Enhancement, Inpainting | ||
Location | Area G | ||
Session Time: | Tuesday, 21 September, 08:00 - 09:30 | ||
Presentation Time: | Tuesday, 21 September, 08:00 - 09:30 | ||
Presentation | Poster | ||
Topic | Image and Video Processing: Restoration and enhancement | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | Poor visibility due to existence of fog and other associated particles in the atmosphere is the most fundamental problem for current vision applications. Recently, techniques for visibility enhancement of images have received a significant attention. However, validation of the existing techniques remains scare due to the lack of balanced distribution on the existing datasets. In this paper, a newly designed dataset entitled “SAMEER-TU Outdoor Dataset” is proposed. The dataset contains 5892 images of urban scenes in fog, poor illumination and clear conditions. Also, ground truths are provided in terms of meteorological weather parameters and corresponding clear scene images of the degraded images. On the designed dataset, quantitative analysis of existing visibility enhancement techniques (i.e., conventional and deep learning techniques) are performed based on qualitative evaluation metrics. It comes as no surprise that the existing visibility enhancement techniques and there still existing significant for further improvement. |