Progressive image transmission using a self-supervised back-propagation neural network

new technique for progressive image transmission (PIT) is presented that uses a self-supervised back-propagation neural network discrete cosine transform. The transmission sequence is determined using a back-propagation neural network (BPNN) feature importance function. Simulation results show that the PlTsystem can be successfully implemented using BPNN. Veiy good intermediate images are obtained at reasonable bit rates.