Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Statistical modeling of Synthetic Aperture Radar (SAR) images is an important tool for image processing and interpretation, because it can contribute to a better understanding of the terrain electromagnetic scattering mechanisms. To that end, the G 0  I  distribution is able to characterize a large number of targets. This distribution depends on three parameters: texture, scale, and the number of looks. The first has received special attention in the literature because it is closely related number of elementary backscatterers in the scene.   compare estimators for the texture parameter in the single look case. The single-look G 0  I  law is a Pareto distribution whose tail index is related to the texture parameter, so  propose a tail index estimator. The estimators performance is analyzed in terms convergence, bias and mean squared error. Then  apply these estimators to actual data.
['Debora S. Chan', 'Julia Cassetti', 'Alejandro C. Frery']
I am writing a research paper on a idea Texture parameter estimation in monopolarized SAR imagery, for the single look case, using extreme value theory
[{"from": "human", "value": "I am writing a research paper on a idea Texture parameter estimation in monopolarized SAR imagery, for the single look case, using extreme value theory"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Statistical modeling of Synthetic Aperture Radar (SAR) images is an important tool for image processing and interpretation, because it can contribute to a better understanding of the terrain electromagnetic scattering mechanisms. To that end, the G 0  I  distribution is able to characterize a large number of targets. This distribution depends on three parameters: texture, scale, and the number of looks. The first has received special attention in the literature because it is closely related number of elementary backscatterers in the scene.   compare estimators for the texture parameter in the single look case. The single-look G 0  I  law is a Pareto distribution whose tail index is related to the texture parameter, so  propose a tail index estimator. The estimators performance is analyzed in terms convergence, bias and mean squared error. Then  apply these estimators to actual data."}]