Hyperspectral remote sesing images have the advantages of super multi-band

high spectral resolution

abundant amount of information

and so on. At the same time

it is a tough task for real-time processing of anomaly detection. The hyperspectral real-time anomaly detection algorithm based on Cholesky decomposition solves the real-time problem well

while the graphics processing unit（ GPU） parallel optimization design is more efficient. The experimental result shows that the proposed optimal design significantly enhance the efficiency of computation

while assuring the precision of detection. This new parallel algorithm acceleration ratio reaches up to 3. 14 times

which shows that the GPU-based parallel optimization algorithm can meet the application requirements of real-time processing of hyperspectral remote sensing image well.