Title :
Progressive image transmission using self-supervised backpropagation neural network
Author :
Gong, Wei ; Rao, K.R. ; Manry, M.T.
Author_Institution :
Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
Abstract :
A novel technique for progressive image transmission (PIT) is presented which uses a self-supervised backpropagation neural network discrete cosine transform. The transmission sequence is determined using a backpropagation neural network (BPNN) feature importance function. Simulation results show that the PIT system can be successfully implemented using BPNN. Very good intermediate images are obtained at reasonable bit rates
Keywords :
neural nets; picture processing; transforms; visual communication; DCT; bit rates; discrete cosine transform; feature importance function; image processing; intermediate images; progressive image transmission; self-supervised backpropagation neural network; transmission sequence; visual telecommunication services; Backpropagation; Bit rate; Discrete cosine transforms; Electronic mail; HDTV; Image communication; Kernel; Medical simulation; Neural networks; Teleconferencing;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186624
