TY - GEN
T1 - Data dependent wavelet filtering for lossless image compression
AU - Pogrebnyak, Oleksiy
AU - Ramírez, Pablo Manrique
AU - Fernandez, Luis Pastor Sanchez
AU - Luna, Roberto Sánchez
PY - 2005
Y1 - 2005
N2 - A data dependent wavelet transform based on the modified lifting scheme is presented. The algorithm is based on the wavelet filters derived from a generalized lifting scheme. The proposed framework for the lifting scheme permits to obtain easily different wavelet FIR filter coefficients in the case of the (∼N, N) lifting. To improve the performance of the lifting filters the presented technique additionally realizes IIR filtering by means of the feedback to the already calculated wavelet coefficients. The perfect image restoration in this case is obtained employing the particular features of the lifting scheme. Changing wavelet FIR filter order and/or FIR and IIR coefficients, one can obtain the filter frequency response that match better to the image data than the standard lifting filters, resulting in higher data compression rate. The designed algorithm was tested on different images. The obtained simulation results show that the proposed method performs better in data compression for various images in comparison to the standard technique resulting in significant savings in compressed data length.
AB - A data dependent wavelet transform based on the modified lifting scheme is presented. The algorithm is based on the wavelet filters derived from a generalized lifting scheme. The proposed framework for the lifting scheme permits to obtain easily different wavelet FIR filter coefficients in the case of the (∼N, N) lifting. To improve the performance of the lifting filters the presented technique additionally realizes IIR filtering by means of the feedback to the already calculated wavelet coefficients. The perfect image restoration in this case is obtained employing the particular features of the lifting scheme. Changing wavelet FIR filter order and/or FIR and IIR coefficients, one can obtain the filter frequency response that match better to the image data than the standard lifting filters, resulting in higher data compression rate. The designed algorithm was tested on different images. The obtained simulation results show that the proposed method performs better in data compression for various images in comparison to the standard technique resulting in significant savings in compressed data length.
KW - Adaptive compression
KW - Image processing
KW - Lifting scheme
KW - Wavelets
UR - http://www.scopus.com/inward/record.url?scp=33745348018&partnerID=8YFLogxK
U2 - 10.1007/11578079_30
DO - 10.1007/11578079_30
M3 - Contribución a la conferencia
SN - 3540298509
SN - 9783540298502
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 285
EP - 294
BT - Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings
T2 - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005
Y2 - 15 November 2005 through 18 November 2005
ER -