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A universal image coding approach using sparse steered Mixture-of-Experts regression
2016 IEEE International Conference on Image Processing (ICIP)
To refer to or to cite this work, please use the citation to the published version: Verhack, R., Sikora, T., Lange, L., Van Wallendael, G., and Lambert, P. (2016). A universal image coding approach using sparse steered Mixture-of-Experts regression. ABSTRACT Our challenge is the design of a "universal" bit-efficient image compression approach. The prime goal is to allow reconstruction of images with high quality. In addition, we attempt to design the coder and decoder "universal", such thatdoi:10.1109/icip.2016.7532737 dblp:conf/icip/VerhackSLWL16 fatcat:b2fxpw5tnfdeddrql5jdoghz7u