TY - GEN

T1 - Combining neural networks and the wavelet transform for image compression

AU - Denk, Tracy

AU - Parhi, Keshab K.

AU - Cherkassky, Vladimir

PY - 1993/1/1

Y1 - 1993/1/1

N2 - This paper presents a new image compression scheme which uses the wavelet transform and neural networks. Image compression is performed in three steps. First, the image is decomposed at different scales, using the wavelet transform, to obtain an orthogonal wavelet representation of the image. Second, the wavelet coefficients are divided into vectors, which are projected onto a subspace using a neural network. The number of coefficients required to represent the vector in the subspace is less than the number of coefficients required to represent the original vector, resulting in data compression. Finally, the coefficients which project the vectors of wavelet coefficients onto the subspace are quantized and entropy coded. The advantages of various quantization schemes are discussed. Using these techniques, we obtain 32 to 1 compression at peak SNR of 29 dB for the 'lenna' image.

AB - This paper presents a new image compression scheme which uses the wavelet transform and neural networks. Image compression is performed in three steps. First, the image is decomposed at different scales, using the wavelet transform, to obtain an orthogonal wavelet representation of the image. Second, the wavelet coefficients are divided into vectors, which are projected onto a subspace using a neural network. The number of coefficients required to represent the vector in the subspace is less than the number of coefficients required to represent the original vector, resulting in data compression. Finally, the coefficients which project the vectors of wavelet coefficients onto the subspace are quantized and entropy coded. The advantages of various quantization schemes are discussed. Using these techniques, we obtain 32 to 1 compression at peak SNR of 29 dB for the 'lenna' image.

UR - http://www.scopus.com/inward/record.url?scp=0027297459&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027297459&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0027297459

SN - 0780309464

T3 - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

SP - I-637-I-640

BT - Plenary, Special, Audio, Underwater Acoustics, VLSI, Neural Networks

PB - Publ by IEEE

T2 - 1993 IEEE International Conference on Acoustics, Speech and Signal Processing

Y2 - 27 April 1993 through 30 April 1993

ER -