Computer Vision, Graphics, and Image Processing
Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Image Understanding
Morphological multiscale segmentation for image coding
Proceedings of of the IEEE winter workshop on Nonlinear digital signal processing
Digital Pictures: Representation and Compression
Digital Pictures: Representation and Compression
A lossless morphological sampling scheme for segmented image compression
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
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In this paper a new image coding scheme based on the uniform morphological sampling is presented. In the proposed algorithm, the image is sub-sampled uniformly using a sampling grid of squares of size 4 in Heijmans method. The sampling process is equivalent to decomposing the image into 4×4 blocks and each block is represented by its minimum intensity (sample value). The residual blocks are then classified into uniform and non-uniform blocks according to a discrete gradient. The uniform blocks are represented by their mean value. Each non-uniform block is represented by its minimum value and a block (vector) chosen among a predetermined codebook blocks (vectors). The uniform and non-uniform blocks are coded by a different number of bits. Also, a hierarchical version is proposed which provides a higher compression ratio for an approximately equivalent visual quality. Several experiments are made, and compression ratios of 22.64 to 25.19 for a good visual quality of reconstructed images are obtained.