Title :
Image compression with geometrical wavelets
Author :
Le Pennec, E. ; Mallat, Stephane
Author_Institution :
Centre de Math. Appliquees, Ecole Polytech., Palaiseau, France
Abstract :
We introduce a sparse image representation that takes advantage of the geometrical regularity of edges in images. A new class of one-dimensional wavelet orthonormal bases, called foveal wavelets, are introduced to detect and reconstruct singularities. Foveal wavelets are extended in two dimensions, to follow the geometry of arbitrary curves. The resulting two dimensional “bandelets” define orthonormal families that can restore close approximations of regular edges with few non-zero coefficients. A double layer image coding algorithm is described. Edges are coded with quantized bandelet coefficients, and a smooth residual image is coded in a standard two-dimensional wavelet basis
Keywords :
data compression; edge detection; geometric codes; image coding; image representation; transform coding; wavelet transforms; 2D wavelet basis; arbitrary curves; double layer image coding algorithm; foveal wavelets; geometrical regularity; geometrical wavelets; image compression; nonzero coefficients; one-dimensional wavelet orthonormal bases; quantized bandelet coefficients; regular edges; singularities detection; singularities reconstruction; smooth residual image; sparse image representation; two dimensional bandelets; Code standards; Continuous wavelet transforms; Geometry; Image coding; Image edge detection; Image reconstruction; Image representation; Image restoration; Rate distortion theory; Wavelet transforms;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.901045