Abstract
The use of all types of Radio image, Echo, MRI... poses a major problem of storage and of filing as example a hospital of 200 beds produces each year 875 Gb of data and so of such images must be transmitted via a network; the duration of transmission is often too long; as a stage has all these problems; compression becomes an operation imperative and necessary. The techniques of fractal image compression are still suffering from very significant coding time. We propose a new optimization approach; it is a hybridization of the SPIHT coding method and algorithm type Jacquin. After applying the method of SPIHT image compression using Daubechies (9-7) Wavelets, the goal is to seek the most significant factors in the transformed image (scalar quantization) to encode only this latter; which serves to minimize the compression time. Our approach was tested on mammography images of MIAS data base.
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Soumya, B., Bouabdellah, G. (2011). Compression of Mammography Image by SPIHT and Fractals. In: Travieso-González, C.M., Alonso-Hernández, J.B. (eds) Advances in Nonlinear Speech Processing. NOLISP 2011. Lecture Notes in Computer Science(), vol 7015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25020-0_20
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DOI: https://doi.org/10.1007/978-3-642-25020-0_20
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