13 April 2018 Optimization of the hierarchical interpolator for image compression
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Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961C (2018) https://doi.org/10.1117/12.2309527
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Abstract
Hierarchical interpolation of images is investigated in the problem of image compression. A new approach is proposed for optimizing the adaptive interpolator for hierarchical compression. This approach is based on optimizing the entropy of the compressed signal. This approach is more adequate to the compression problem than the known approach based on optimization of the interpolation error. The optimization algorithm for the adaptive interpolator is proposed on the basis of the proposed approach. The theoretical estimation of the computational complexity of the proposed interpolator is calculated. A comparison of this complexity with the complexity of other interpolators is performed. The advantage of the proposed interpolator over known interpolators is investigated experimentally. The win is calculated according to the size of the archive file. Recommendations for the use of the proposed interpolator are formulated.
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Mikhail Gashnikov, "Optimization of the hierarchical interpolator for image compression", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961C (13 April 2018); doi: 10.1117/12.2309527; https://doi.org/10.1117/12.2309527
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