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搜索结果: 1-10 共查到Spectral Unmixing相关记录10条 . 查询时间(0.11 秒)
Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied....
Spectral unmixing of hyperspectral data often fails to select some minerals and rocks having flat spectra but no diagnostic absorption features as endmembers, even if they are actually important endme...
This paper presents a study about the potential of spectral unmixing of hyperspectral satellite image data for targeting and quantification of mineral content in limestone and bauxite rich areas in so...
In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve...
The linear spectral mixing model is a widely used technique in remote sensing to estimate the fractions of several individual surface components present in an image pixel and the pure reflectance spe...
The expansion of urban areas has a negative impact on the environment. The increase of impervious or sealed surfaces is directly proportional to this expansion. The estimation of sealed surfaces has o...
There are a considerable number of mixed pixels in remotely sensed images. Different sub-pixel analyses have been recently developed correspondingly. A well-known method is linear spectral unmixing wh...
Spectral mixing is inherent in any finite-resolution digital imagery of a heterogeneous surface, so that mixed pixels are inevitably created when multispectral images are scanned. Solving the spectra...
The orbiting cycle and frequent cloud contamination have limited the applications of the moderate-resolution remotely sensed data for detecting rapid land cover changes that are critical to the monito...
Super resolution-based spectral unmixing (SRSU) is a recently developed method for spectral unmixing of remotely sensed imagery, but it is too complex to implement for common users who are interested ...

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