Most compression methods have been developed to minimize mean squared errors. On the other hand, discriminant information required to distinguish between various classes is also vital for applications where hyperspectral images are used for classification. However, the discriminant information may not be well preserved during lossy compression process since it may not be large in energy. To deal with this problem, a hybrid compression method was proposed. In this paper, we propose a method to optimize signal and discriminant information for the hybrid method. Experimental results show some improvement can be achieved by this optimization.
['Sei Jin Youn', 'C.G. Lee']
Optimizing signal and discriminant information for hyperspectral images