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A New Optimized Denoising Method applied to the Spot World Heritage Initiative and its Spot 5 Supermode images

机译:一种新的优化去噪方法应用于“世界自然遗产计划”及其“ 5点超模”图像

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In the context of the Spot World Heritage (SWH) initiative, the long term archive of Spot 1 to 5 satellite data will be reprocessed. This initiative gives the opportunity to increase Spot data quality and production efficiency with the introduction of new state-of-the-art processing methods. In this context, we consider the Spot 5 Supermode processing chain and the introduction of a new denoising method. Our objective is to propose the best denoising method in terms of efficiency and accuracy for the Spot 5 Supermode data production. We report two experimentations that lead to the choice of the Non Local Bayes (NLB) denoising method; it is fast, accurate and remains stable in terms of efficiency and quality for different landscapes and image sizes. We also introduce two optimized versions of the NLB algorithm that increase the computation efficiency by a factor up to 4.
机译:在现货世界遗产(SWH)计划的背景下,将重新加工1至5个卫星数据的长期存档。这项举措使机会通过引入新的最先进的处理方法来提高现货数据质量和生产效率。在这种情况下,我们考虑了现场5个超导加工链和引入新的去噪方法。我们的目标是在现场5 SuperMode数据生产的效率和准确性方面提出最佳去噪方法。我们报告了两项实验,导致非本地贝叶斯(NLB)去噪方法的选择;它在不同景观和图像尺寸的效率和质量方面快速,准确,并且保持稳定。我们还介绍了两种优化版本的NLB算法,可以将计算效率提高了一个最多4个系数。

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