High-spectrum image classification method based on linear prediction cepstrum coefficient
A hyperspectral image and cepstral coefficient technology, applied in the field of spectral data classification, can solve the problems of difficult wide application, poor real-time performance, and high algorithm complexity, and achieve high real-time performance, good classification effect, and low algorithm complexity.
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[0023] Refer to attached figure 1 , the detailed implementation steps of the hyperspectral image spectral classification method based on the linear predictive cepstral coefficient of the present invention are as follows:
[0024] Step 1, read the reference hyperspectral image of the known surface morphology category.
[0025] The reference hyperspectral image adopts the standard spectral library or the hyperspectral image of known ground object types. Such as figure 2 The image shown is the reference hyperspectral image of the known surface morphology category, which comes from the Indina pink image in the airborne infrared imaging spectrometer AVRIS, with a size of 145×145 and a total of 220 bands.
[0026] Step 2, extract the linear predictive cepstral coefficient h of the benchmark hyperspectral data s .
[0027] (2.1) Yes figure 2 The reference hyperspectral data shown is average filtered, that is, spectral noise is filtered to reduce the interference of spectral no...
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