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- W2069148977 abstract "Abstract The creation of large area image mosaics from moderate and high resolution (less than 100 m) satellite data presents special challenges particularly in the achievement of radiometric continuity (i.e. seamlessness). Typically, scenes must be employed which have been acquired over a broad time window and which therefore exhibit a diversity of atmospheric and seasonal conditions. Radiometric normalization has been achieved using a variety of empirical techniques, the success of which has been assessed solely through visual inspection. If mosaics are to become viable quantitative products, a rigorous understanding of their radiometric fidelity is required. This paper attempts to address some aspects of this issue. A suite of assessment tools are developed to derive radiometric quality measures from grey level scattergrams of inter-scene overlap regions. First, a clustering technique is proposed to edit out overlap samples which are either contaminated by cloud cover or which exhibit significant surface cover differences. The remaining control sample, which is used to define the relative radiometric normalization between the two overlapping scenes in question, can then be analyzed to provide a further measure of ‘information continuity’. A preferred normalization strategy is one in which a single set of coefficients is applied to all pixels in a scene. Methods are presented to assess the errors associated with this approximation, namely, (1) the magnitude of residual intra-scene radiometric trends which, although subtle on the scale of a scene, can give rise to significant radiometric variations in large scale mosaics, and (2) the uncertainty in characterizing full scene radiometry based on information derived from a set of independent partial overlaps with neighbouring scenes. Example results are presented for an extensive Landsat MSS data set of the forested regions of northwestern Ontario." @default.
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- W2069148977 title "Assessing the radiometric fidelity of high resolution satellite image mosaics" @default.
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- W2069148977 doi "https://doi.org/10.1016/s0924-2716(97)00016-6" @default.
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