Spherical coding algorithm for wavelet image compression
Autor: | Michael T. Orchard, Hasan Fehmi Ateş |
---|---|
Přispěvatelé: | Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering, Ateş, Hasan Fehmi |
Rok vydání: | 2009 |
Předmět: |
Adaptive coding
Adaptive methods Coding algorithms Image compression Compaction Wavelet subband Highest resolutions Coder Direct measures Wavelet coders Wavelet packet decomposition Wavelet Local energies Computer vision Coding efficiencies Energy resolution Mathematics Wavelet image compression Coding Image regions Sub bands Wavelet transform Wavelet coefficients Bit rate Spherical coding algorithm Computer Graphics and Computer-Aided Design Wavelet domain Algorithm Data compression Spatial energies Stationary wavelet transform ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Cascade algorithm Data_CODINGANDINFORMATIONTHEORY Spatially adaptive Energy measurement Wavelet transforms Computer Science::Multimedia Bit rates Adaptive frameworks business.industry PSNR Image coding Codecs Image Artificial intelligence business Software |
Zdroj: | IEEE Transactions on Image Processing |
ISSN: | 1057-7149 |
Popis: | This work was supported in part by the National Science Foundation under Grant DMS9872890 and in part by the Isik University BAP-05B302 Grant. In recent literature, there exist many high-performance wavelet coders that use different spatially adaptive coding techniques in order to exploit the spatial energy compaction property of the wavelet transform. Two crucial issues in adaptive methods are the level of flexibility and the coding efficiency achieved while modeling different image regions and allocating bitrate within the wavelet subbands. In this paper, we introduce the "spherical coder," which provides a new adaptive framework for handling these issues in a simple and effective manner. The coder uses local energy as a direct measure to differentiate between parts of the wavelet subband and to decide how to allocate the available bitrate. As local energy becomes available at finer resolutions, i.e., in smaller size windows, the coder automatically updates its decisions about how to spend the bitrate. We use a hierarchical set of variables to specify and code the local energy up to the highest resolution, i.e., the energy of individual wavelet coefficients. The overall scheme is nonredundant, meaning that the subband information is conveyed using this equivalent set of variables without the need for any side parameters. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature. Isik University National Science Foundation Publisher's Version Author Post Print Q1 WOS:000265091700009 PubMed ID: 19342336 |
Databáze: | OpenAIRE |
Externí odkaz: |