TY - JOUR
T1 - Adaptive wavelet transform algorithm for image compression applications
AU - Pogrebnya, Oleksiy
AU - Ramírez, Pablo Manrique
PY - 2003
Y1 - 2003
N2 - A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the ( Ñ, N ) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images, The proposed adaptive transform algorithm can be used for image/signal compression and noise suppression.
AB - A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the ( Ñ, N ) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images, The proposed adaptive transform algorithm can be used for image/signal compression and noise suppression.
KW - Image processing
KW - Lifting scheme
KW - Lossless compression
KW - Wavelets
UR - http://www.scopus.com/inward/record.url?scp=2342562471&partnerID=8YFLogxK
U2 - 10.1117/12.504092
DO - 10.1117/12.504092
M3 - Artículo de la conferencia
AN - SCOPUS:2342562471
SN - 0277-786X
VL - 5203
SP - 623
EP - 630
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
T2 - Applications of Digital Image Processing XXVI
Y2 - 5 August 2003 through 8 August 2003
ER -