Abstract
The Contourlet Transform (CT) can capture the intrinsic geometrical structure of an image. The CT is a redundant transform, and for coding applications this can be a disadvantage. In order to avoid the contourlet redundancy we change the pyramidal stage by a multiscale stage. The new non redundant transform is called: The Wavelet Based Contourlet Transform. We take the advantages offered by the new transform to build a novel feature preserving image coder. The preservation is made both: by a stage of feature definition and extraction and by a proposed modified version of the SPIHT coder. SPIHT modification allows selecting a transform coefficient not only by magnitude, but as pertaining to a feature of interest map. We present tests in order to demonstrate the good performance of the coder. Finally, we compare the results with other existing methods. The coder designed performs well even at very low bit rates.
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© 2007 Springer-Verlag Berlin Heidelberg
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Vergara Villegas, O.O., Cruz Sánchez, V.G. (2007). The Wavelet Based Contourlet Transform and Its Application to Feature Preserving Image Coding. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_56
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DOI: https://doi.org/10.1007/978-3-540-76631-5_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76630-8
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