Hyperspectral Image Compression Method

Hyperspectral image coding has been widely used in both military and civilian fields.The challenge that this technique faces is high performance compression of massively large sized data sets.Therefore low complexity,low memory requirement and high performance hyperspectral image coding method become much meaningful.In this dissertation,hyperspectral image coding method is studied.First,the spatial and spectral correlation of hyperspectral image is investigated.Secondly,a low complexity reversible integer Karhunen-Lo e ve transform(KLT)is studied. Pseudorandom uniform sampling is used to reduce the calculation of the covariance matrix in KLT,and the matrix factorization of transform matrix is used to research on reversible integer KLT.Then,two-dimensional wavelet transform,one-dimensional low complexity integer reversible KLT and three-dimensional Set Partitioning in Hierarchical Threes(3D-SPIHT)encoding method are combined to form hyperspectral image compression system.Finally,the experimental results demonstrate that this compression system can achieve good compression performance.