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Development of a robust haze removal algorithm: assessment using temporally invariant targets

A robust haze-removal algorithm based on the Haze Optimized Transformation (HOT) is applied to ETM+ imagery. Its effectiveness is evaluated using temporally invariant targets identified in a multi-temporal data set of scenes of WRS-2 Path15/Row29. In the data set, clear scenes serve as 'benchmarks' against which the effectiveness of haze removal can be assessed. In the quantitative assessment, two hundred coniferous forest patches were randomly sampled and served as 'benchmark' targets since they exhibit both spatial and temporal radiometric invariance on clear data. Comparisons were made of the radiometric characteristics of the patch population in hazy vs. de-hazed and de-hazed vs. clear image pairs. Results show that image contaminated by low to moderate haze can be significantly improved. Reductions of 20 to 90% in intra-scene radiometric dispersion have been achieved with the de-hazed scenes exhibiting residual dispersion levels comparable to those of the benchmark scenes.