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Establishing an objective basis for image compositing in satellite oceanography

机译:为卫星海洋学中的图像合成建立客观基础

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This study strives to establish an objective basis for image compositing in satellite oceanography. Image compositing is a powerful technique for cloud filtering that often emphasizes cloud clearing at the expense of obtaining synoptic coverage. Although incomplete cloud removal in image compositing is readily apparent, the loss of synopticity, often, is not. Consequently, the primary goal of image compositing should be to obtain the greatest amount of cloud-free coverage or clarity in a period short enough that synopticity, to a significant degree, is preserved. To illustrate the process of image compositing and the problems associated with it, we selected a region off the coast of California and constructed two 16-day image composites, one, during the spring, and the second, during the summer of 2006, using Advanced Very High Resolution Radiometer (AVHRR) InfraRed (IR) satellite imagery. Based on the results of cloud clearing for these two 16-day sequences, rapid cloud clearing occurred up to day 4 or 5, followed by much slower cloud clearing out to day 16, suggesting an explicit basis for the growth in cloud clearing. By day 16, the cloud clearing had, in most cases, exceeded 95%. Based on these results, a shorter compositing period could have been employed without a significant loss in clarity. A method for establishing an objective basis for selecting the period for image compositing is illustrated using observed data. The loss in synopticity, which, in principle, could be estimated from pattern correlations between the images in the composite, was estimated from a separate time series of SST since the loss of synopticity, in our approach, is only a function of time. The autocorrelation function of the detrended residuals provided the decorrelation time scale and the basis for the decay process, which, together, define the loss of synopticity. The results show that (1) the loss of synopticity and the gain in clarity are inversely related, (2) an objective basis for selecting a compositing period corresponds to the day number where the decay and growth curves for synopticity and clarity intersect, and (3), in this case, the point of intersection occurred 3.2 days into the compositing period. By applying simple mathematics it was shown that the intersection time for the loss in synopticity and the growth in clarity is directly proportional to the initial conditions required to specify the clarity at the beginning of the compositing period, and inversely proportional to the sum of the rates of growth for clarity and the loss in synopticity. Finally, we consider these results to be preliminary in nature, and, as a result, hope that future work will bring forth significant improvements in the approach outlined in this study.
机译:这项研究致力于为卫星海洋学中的图像合成建立客观的基础。图像合成是一种强大的云过滤技术,通常会以清除天气覆盖范围为代价来强调云清除。尽管很容易在图像合成中去除不完全的云,但是通常并不会失去同调性。因此,图像合成的主要目标应该是在足够短的时间内获得最大程度的无云覆盖率或清晰度,以便在很大程度上保持同步性。为了说明图像合成的过程以及与之相关的问题,我们选择了加利福尼亚海岸附近的一个区域,并使用“高级”功能构建了两个16天的图像合成物,一个在春季,第二个在2006年夏季。超高分辨率辐射计(AVHRR)红外(IR)卫星图像。根据这两个为期16天的序列清除云的结果,直到第4天或第5天,才发生了快速的云清除,而到第16天的清除速度却慢得多,这为清除云的增长提供了明确的基础。到第16天,在大多数情况下,云清除已超过95%。基于这些结果,可以采用较短的合成周期而不会明显损失清晰度。使用观察到的数据说明了一种建立客观基础以选择图像合成周期的方法。原则上,可以从合成图像中图像之间的模式相关性来估计同步丢失,这是从SST的单独时间序列中估计出来的,因为在我们的方法中,同步丢失仅是时间的函数。去趋势残差的自相关函数提供了去相关的时间尺度和衰减过程的基础,它们共同定义了同质性的损失。结果表明(1)同质性的丧失与清晰度的提高成反比关系,(2)选择合成周期的客观依据对应于同质性和清晰度的衰减曲线与增长曲线相交的天数,以及( 3),在这种情况下,相交点发生在合成期间的3.2天。通过应用简单的数学方法,可以看出,失去同调度和清晰度增长的交点时间与合成期间开始时指定清晰度所需的初始条件成正比,而与比率之和成反比增长的目的是为了清楚起见,而失去同调。最后,我们认为这些结果本质上是初步的,因此,希望将来的工作将对本研究概述的方法带来重大改进。

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