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