document: Multilayered image representation : application to image compression The main contribution of this work is a new paradigm for image representation and image compression . We describe a new multilayered representation technique for images . An image is parsed into a superposition of coherent layers : piecewise smooth regions layer , textures layer , etc. . The multilayered decomposition algorithm consists in a cascade of compressions applied successively to the image itself and to the residuals that resulted from the previous compressions . During each iteration of the algorithm , we code the residual part in a lossy way : we only retain the most significant structures of the residual part , which results in a sparse representation . Each layer is encoded independently with a different transform , or basis , at a different bitrate , and the combination of the compressed layers can always be reconstructed in a meaningful way . The strength of the multilayer approach comes from the fact that different sets of basis functions complement each others : some of the basis functions will give reasonable account of the large trend of the data , while others will catch the local transients , or the oscillatory patterns . This multilayered representation has a lot of beautiful applications in image understanding , and image and video coding . We have implemented the algorithm and we have studied its capabilities
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