Wavelet-based image compression by hierarchical quantization indexing
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Dosyalar
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet 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. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature.
Açıklama
Anahtar Kelimeler
Indexes, Encoding, PSNR, Abstracts, Bit rate, Complexity theory, Data compression, Image classification, Image coding, Indexing, Wavelet transforms, Wavelet-based image compression, Hierarchical quantization indexing, Efficient coding, Quantized wavelet coefficients, Hierarchical classification map, Rate-distortion cost analysis, Class assignments, Cost analysis, Hierarchical classification, Membership information, Quantization index, Rate distortions, Wavelet coefficients, Wavelet subbands, Cost accounting, Image compression, Optimization, Signal processing, Forestry
Kaynak
European Signal Processing Conference
WoS Q Değeri
Scopus Q Değeri
N/A
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Sayı
Künye
Ateş, H. F. & Tamer, E. (2009). Wavelet-based image compression by hierarchical quantization indexing. Paper presented at the 2117-2121.
