Subband image coding using watershed and watercourse lines of the wavelet transform

Reports progress in primitive-based image coding using nonorthogonal dyadic wavelets. A 3D isotropic wavelet is used to approximate the difference-of-Gaussians (D-o-G) operator. Convolution of the image with dilated versions of the wavelet produces three band-pass signals that approximate multiscale smoothed second derivatives. An additional convolution of the image with a Gaussian-shaped low-pass wavelet creates a fourth subband signal that preserves low-frequency information not described by the three band-pass signals. The authors show that the original image can be recovered from the watershed and watercourse lines of the three band-pass signals plus the lowpass subband signal. By thresholding the watershed/watercourse representation, subsampling the low-pass subband, and using edge post emphasis, the authors achieve data reduction with little loss of fidelity. Further compression of the watersheds and watercourses is achieved by chain coding their shapes and predictive coding their amplitudes prior to lossless arithmetic coding. Results are presented for grey-level test images at data rates between 0.1 and 0.3 b/pixel