# Approximation and Compression With Sparse Orthonormal Transforms

@article{Sezer2015ApproximationAC, title={Approximation and Compression With Sparse Orthonormal Transforms}, author={Osman Gokhan Sezer and Onur G. Guleryuz and Y{\"u}cel Altunbasak}, journal={IEEE Transactions on Image Processing}, year={2015}, volume={24}, pages={2328-2343} }

We propose a new transform design method that targets the generation of compression-optimized transforms for next-generation multimedia applications. The fundamental idea behind transform compression is to exploit regularity within signals such that redundancy is minimized subject to a fidelity cost. Multimedia signals, in particular images and video, are well known to contain a diverse set of localized structures, leading to many different types of regularity and to nonstationary signal…

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