Signal Processing - Signal processing with heavy-tailed models
Computer vision based method for real-time fire and flame detection
Pattern Recognition Letters
Combining Seminorms in Adaptive Lifting Schemes and Applications to Image Analysis and Compression
Journal of Mathematical Imaging and Vision
Block-based adaptive vector lifting schemes for multichannel image coding
Journal on Image and Video Processing
An edge-sensing predictor in wavelet lifting structures for lossless image coding
Journal on Image and Video Processing
Adapted generalized lifting schemes for scalable lossless image coding
Signal Processing
A reconfigurable systolic array architecture for multicarrier wireless and multirate applications
International Journal of Reconfigurable Computing
3D Model compression using Connectivity-Guided Adaptive Wavelet Transform built into 2D SPIHT
Journal of Visual Communication and Image Representation
Machine Graphics & Vision International Journal
Adaptive 2-D wavelet transform based on the lifting scheme with preserved vanishing moments
IEEE Transactions on Image Processing
Directional filtering transform for image/intra-frame compression
IEEE Transactions on Image Processing
MUSCLE'11 Proceedings of the 2011 international conference on Computational Intelligence for Multimedia Understanding
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Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented