Beyond Single-Image Dehazing Benchmarking PROJECT TITLE : Benchmarking Single-Image Dehazing and Beyond ABSTRACT: New large-scale benchmarks termed REalistic Single Image DEhazing (RSIDE) have been developed to evaluate the performance of single-image dehazing algorithms, including both synthetic and real-world hazy images (RESIDE). Five subsets of data and visual content are highlighted in RESIDE for different training and evaluation objectives. A wide range of evaluation criteria for dehazing algorithms, from full-reference metrics, to no-reference metrics, subjective evaluation, and the innovative task-driven evaluation, are included in this study. Reside experiments give information on the comparisons and limitations of current dehazing methods, as well as interesting new avenues. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Multi-class cell segmentation using Bayesian polytrees with learned deep features Anisotropic Fractal Model and Phase Retrieval Algorithm for Blind Deblurring of Natural Stochastic Textures
