Hierarchical quantization indexing for wavelet and wavelet packet image coding
| Autor: | Hasan Fehmi Ateş, Engin Tamer |
|---|---|
| Přispěvatelé: | Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering, Ateş, Hasan Fehmi, Tamer, Engin |
| Rok vydání: | 2010 |
| Předmět: |
Discrete wavelet transform
Wavelet subbands Quantization index Stationary wavelet transform ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Cascade algorithm Data_CODINGANDINFORMATIONTHEORY Wavelets Adaptive arithmetic coding Wavelet packets Wavelet packet decomposition Space-frequency quantization Wavelet Hierarchy Cost analysis Electrical and Electronic Engineering Rate distortions Class assignments Mathematics Second-generation wavelet transform Image coding Wavelet transform Cost accounting Classification Hierarchical classification Wavelet packet coefficient Coding efficiency Arithmetic coding Algorithm Signal Processing Membership information Feature extraction Computer Vision and Pattern Recognition Set Visual communication Software |
| Zdroj: | Signal Processing: Image Communication. 25:111-120 |
| ISSN: | 0923-5965 |
| DOI: | 10.1016/j.image.2009.09.007 |
| Popis: | This research was supported by Isik University BAP-05B302 Grant In this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger Subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature. Isik University Publisher's Version Q2 WOS:000275582300004 |
| Databáze: | OpenAIRE |
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