کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
413042 | 679713 | 2008 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A new sub-pixel mapping algorithm based on a BP neural network with an observation model A new sub-pixel mapping algorithm based on a BP neural network with an observation model](/preview/png/413042.png)
The mixed pixel is a common problem in remote sensing classification. Even though the composition of these pixels for different classes can be estimated with a pixel un-mixing model, the output provides no indication of how such classes are distributed spatially within these pixels. Sub-pixel mapping is a technique designed to use the output information with the assumption of spatial dependence to obtain a sharpened image. Pixels are divided into sub-pixels, representing the land cover class fractions. This paper proposes a new algorithm based on a back-propagation (BP) network combined with an observation model. This method provides an effective method of obtaining the sub-pixel mapping result and can provide an approximation of the reference classification image. With the upscale factor, the model was tested on both a simple artificial image and a remote sensing image, and the results confirm that the proposed mapping algorithm has better performance than the original BPNN model.
Journal: Neurocomputing - Volume 71, Issues 10–12, June 2008, Pages 2046–2054