Image data compression using cubic convolution spline interpolation

A new cubic convolution spline interpolation (CCSI )for both one-dimensional (1-D) and two-dimensional (2-D) signals is developed in order to subsample signal and image compression data. The CCSI yields a very accurate algorithm for smoothing. It is also shown that this new and fast smoothing filter...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 9; no. 11; pp. 1988 - 1995
Main Authors Truong, T.K., Wang, L.J., Reed, I.S., Hsieh, W.S.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.11.2000
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Convolution
Data compression
Exact sciences and technology
Image coding
Image compression
Image processing
Image reconstruction
Information, signal and communications theory
Interpolation
JPEG encoders-decoders
Pattern recognition. Digital image processing. Computational geometry
Quantization
Radiofrequency interference
Signal processing
Smoothing
Smoothing methods
Spline
Splines
Telecommunications and information theory
Transform coding
Interpolation
Convolution
Image processing
Coding
Least squares method
Data compression
Algorithm
Cubic spline
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Summary:A new cubic convolution spline interpolation (CCSI )for both one-dimensional (1-D) and two-dimensional (2-D) signals is developed in order to subsample signal and image compression data. The CCSI yields a very accurate algorithm for smoothing. It is also shown that this new and fast smoothing filter for CCSI can be used with the JPEG standard to design an improved JPEG encoder-decoder for a high compression ratio.
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ISSN:1057-7149
1941-0042
DOI:10.1109/83.877222