102results about How to "Improve approximation accuracy" patented technology

The invention discloses a hyperspectral image classification method based on MNF (Minimum Noise Fraction) transform in combination with extended attribute filtering. The method comprises the steps of 1) performing MNF transform to a hyperspectral remote sensing image; 2) selecting MNF component number and selecting the MNF component number to be reserved according to two constraints, i.e. the characteristic value of band number and the gradient of the characteristic values of adjacent bands; 3) executing EAP (Extended Attribute Profile) operation to each MNF component; 4) stacking the image attribute open profile and the attribute closed profile of each MNF component and the component and performing classification by adopting a K-type SVM (Support Vector Machine) to obtain a final hyperspectral classified image. The method can realize noise reduction through MNF and can effectively reduce the dimensionality of hyperspectral data at the same time. On the basis, spectral information after dimensionality reduction and texture information obtained after EAP filtering are combined, then the characteristics that the K-type SVM can reduce the computation cost and simultaneously has performance similar to an RBF (Radial Basis Function) kernel are utilized and the classification accuracy of the hyperspectral remote sensing image is improved.