A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
SPIHT image compression without lists
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
An experiment on texture segmentation using modulated wavelets
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
The multicomponent AM-FM image representation
IEEE Transactions on Image Processing
Significance-linked connected component analysis for wavelet image coding
IEEE Transactions on Image Processing
Image coding based on a morphological representation of wavelet data
IEEE Transactions on Image Processing
Multidimensional quasi-eigenfunction approximations and multicomponent AM-FM models
IEEE Transactions on Image Processing
Texture segmentation using modulated wavelet transform
IEEE Transactions on Image Processing
A perceptually lossless, model-based, texture compression technique
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Image coding with modulated wavelets
Pattern Recognition Letters
| Hi-index | 0.10 |
In this paper, a new, called the adaptive modulated wavelet transform (AMWT) image representation is presented. One of the attractive features is that the informative instantaneous frequencies of images can be taken into account to improve the representation performance via adaptation of the modulating frequencies involved. The transform coefficients in both wavelet and modulated wavelet domains are uniformly quantized with several quantization levels. The computed peak signal-to-noise ratio values and entropies are used as rate distortion curves for performance comparison. Experimental results show that AMWT out performs wavelet transform for representing images containing textures with rapid variation in grays.