The invention discloses a hyperspectral image
lossless compression method based on the RKLT and principal component selection and belongs to the technical field of
remote sensing hyperspectral image compression. The hyperspectral image
lossless compression method based on the RKLT and principal component selection solves the problem that when an existing KLT method is used for hyperspectral image
lossless compression, generated
floating point number coefficients are not favorable for
processing on hardware. According to the technical scheme, a hyperspectral image is converted into a 2D matrix from a 3D matrix; a
transformation matrix is decomposed into four integer matrixes and transformation coefficients through the RKLT; RKLT
reverse transformation is conducted on principal components which are selected from the transformation coefficients; subtracting is conducted on the matrix obtained after
reverse transformation and the original 2D matrix, so that a residual error is obtained; predicting, forward mapping and section coding are conducted on the residual error and an RKLT forward
transformation matrix of the selected principal components, so that a coding
stream is formed; the
transformation matrix generated by the KLT is stored into an RAW file, and the RAW file and the coding
stream obtained in the last step serve as compressed data to be transmitted to a compression end; the number of the optimal principal components needing to be selected is found through a searching method. The hyperspectral image lossless
compression method is suitable for conducting lossless compression on the hyperspectral image.