A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Computation
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Wavelets and filter banks: theory and design
IEEE Transactions on Signal Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Wavelet transforms in a JPEG-like image coder
IEEE Transactions on Circuits and Systems for Video Technology
Combining support vector machine learning with the discrete cosine transform in image compression
IEEE Transactions on Neural Networks
Perceptual adaptive insensitivity for support vector machine image coding
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
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This paper presents a practical and effective image compression system based on wavelet decomposition and RVM regression for compressing still images. Support vector machine (SVM)-based approaches have been recently proposed for image compression and have raised important interest. In this paper, it is genuinely proposed to use an RVM-based approach for the compression of color images. Since RVMs performance depends to a large degree on the choice of a kernel and kernel parameters, RVM with adaptive wavelet kernels (Adaptive WRVM) is proposed to improve the compression performance of RVM with standard wavelet kernels (Standard WRVM) for image coding. Comparative study of adaptive wavelet kernels and Gaussian kernel is carried out and results showed that adaptive Mexican hat wavelet kernel achieves the best image quality at a given compression ratio. A performance comparison of proposed algorithm with Rki-1, SVM with wavelet kernels (WSVM) and JPEG2000 compression systems is done. It is found that proposed algorithm gives better image quality for a given compression rate in comparison to Rki-1, SVM with wavelet kernels (WSVM) and comparable to JPEG2000.