Signal Processing with Lapped Transforms
Signal Processing with Lapped Transforms
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Image Coding Using Optimized Significance Tree Quantization
DCC '97 Proceedings of the Conference on Data Compression
Fast Progressive Wavelet Coding
DCC '99 Proceedings of the Conference on Data Compression
CREW: Compression with Reversible Embedded Wavelets
DCC '95 Proceedings of the Conference on Data Compression
Line Based, Reduced Memory, Wavelet Image Compression
DCC '98 Proceedings of the Conference on Data Compression
A Low-Complexity Modeling Approach for Embedded Coding of Wavelet Coefficients
DCC '98 Proceedings of the Conference on Data Compression
IEEE Transactions on Signal Processing
A progressive transmission image coder using linear phase uniform filterbanks as block transforms
IEEE Transactions on Image Processing
Wavelet filter evaluation for image compression
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
Geometry clipmaps: terrain rendering using nested regular grids
ACM SIGGRAPH 2004 Papers
High-quality networked terrain rendering from compressed bitstreams
Proceedings of the twelfth international conference on 3D web technology
Reversible data hiding for high quality images using modification of prediction errors
Journal of Systems and Software
Directional lapped transforms for image coding
IEEE Transactions on Image Processing
Real-Time streaming and rendering of terrains
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Lapped transform-based image denoising with the generalised Gaussian prior
International Journal of Computational Vision and Robotics
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We introduce a new image compression algorithm that allows progressive image reconstruction - both in resolution and in fidelity, with a fully embedded bitstream. The algorithm is based on bit-plane entropy coding of reordered transform coefficients, similar to the progressive wavelet codec (PWC) previously introduced.Unlike PWC, however, our new progressive transform coder (PTC) does not use wavelets; it performs the space-frequency decomposition step via a new lapped biorthogonal transform (LBT). PTC achieves a rate vs. distortion performance that is comparable (within 2%) to that of the state-of-the-art SPIHT (set partitioning in hierarchical trees) codec.However, thanks to the use of the LBT, the space-frequency decomposition step in PTC reduces the number of multiplications per pixel by a factor of 2.7, and the number of additions by about 15%, when compared to the fastest possible implementation of the 驴9/7驴 wavelet transform via lifting. Furthermore, since most of the computation in the LBT is in fact performed by a DCT, our PTC codec can make full use of fast software and hardware modules for 1-D and 2-D DCTs.