Image analysis – Image compression or coding – Quantization
Reexamination Certificate
2006-02-21
2006-02-21
Ahmed, Samir (Department: 2623)
Image analysis
Image compression or coding
Quantization
C382S232000
Reexamination Certificate
active
07003171
ABSTRACT:
Fast and efficient data compression can be carried out. Original image data are subjected to wavelet transform. The obtained wavelet-transformed data are classified and bit allocation is determined. Based on the determined bit allocation, the wavelet-transformed data are quantized and quantized data are obtained. The quantized data are classified into 0 data and non-zero data. Binary classification information data indicating this classification are also obtained. The classification information data are coded according to a coding method having a comparatively simple operation, such as Huffman coding and run length coding. The multi-valued, non-zero data are coded according to a coding method having a high compression efficiency although having a comparatively complex operation, such as universal coding and Golomb-Rice coding.
REFERENCES:
IEEE Transactions of Image Processing, vol. 4, Jun. 1995, pp. 725-733, “Image Coding Using Wavelet Transforms and Entropy-Constrained Trellis-Coded Quantization”.
IEEE Transactions on Circuits and Systems for Video Technology, vol. 6, Jun. 1996, pp. 243-250, “A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees”.
Nikkan Kogyo Shimbun Co., May 25, 1981, “Digital Image Signal Processing”, Fukinuke, T.
Shokodo Co., Feb. 25, 1992, “Digital Communication Systems”, Kasahara et al.
Ahmed Samir
Bhatnagar Anand
Fuji Photo Film Co. , Ltd.
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