We present a new approach to lossy storage of the coefficients of wavelet transformed data. While it is common to store the coefficients of largest magnitude (and let all other coefficients be zero), we allow a slightly different set of coefficients to be stored. This brings into play a recently proposed hashing technique that allows space efficient storage and very efficient retrieval of coefficients. Our approach is applied to compression of volumetric data sets. For the ``Visible Man'' volume we obtain up to 80% improvement in compression ratio over previously suggested schemes. Further, the time for accessing a random voxel is quite competitive
We investigate the problem of variable-length compression with random access for stationary and ergo...
The medical imaging requires fast and accurate volume reconstruction. This may be used to evaluate, ...
Advancements in deep learning are often associated with increasing model sizes. The model size drama...
We propose a wavelet based method for compressing volumetric data with little loss in quality. The m...
UnrestrictedVolumetric medical data is a three dimensional view of the object being captured, exampl...
Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress...
Many applications generate an exponentially increasing amount of information or data which needs to ...
Many applications generate an exponentially increasing amount of information or data which needs to ...
Voxel-based segmentation volumes often store a large number of labels and voxels, and the resulting ...
Data in volume form consumes an extraordinary amount of storage space. For efficient storage and tra...
In an image browsing environment there is need for progressively viewing image subregions at various...
AbstractIn an image browsing environment there is need for progressively viewing image subregions at...
textThe problem of archiving photos is becoming increasingly important as image databases are growin...
For successful transmission of massively sequenced images during 4K surveillance operations large am...
Abstract Exascale computing promises quantities of data too large to efficiently store and transfer ...
We investigate the problem of variable-length compression with random access for stationary and ergo...
The medical imaging requires fast and accurate volume reconstruction. This may be used to evaluate, ...
Advancements in deep learning are often associated with increasing model sizes. The model size drama...
We propose a wavelet based method for compressing volumetric data with little loss in quality. The m...
UnrestrictedVolumetric medical data is a three dimensional view of the object being captured, exampl...
Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress...
Many applications generate an exponentially increasing amount of information or data which needs to ...
Many applications generate an exponentially increasing amount of information or data which needs to ...
Voxel-based segmentation volumes often store a large number of labels and voxels, and the resulting ...
Data in volume form consumes an extraordinary amount of storage space. For efficient storage and tra...
In an image browsing environment there is need for progressively viewing image subregions at various...
AbstractIn an image browsing environment there is need for progressively viewing image subregions at...
textThe problem of archiving photos is becoming increasingly important as image databases are growin...
For successful transmission of massively sequenced images during 4K surveillance operations large am...
Abstract Exascale computing promises quantities of data too large to efficiently store and transfer ...
We investigate the problem of variable-length compression with random access for stationary and ergo...
The medical imaging requires fast and accurate volume reconstruction. This may be used to evaluate, ...
Advancements in deep learning are often associated with increasing model sizes. The model size drama...