Image data compression using cubic convolution spline interpolation

• Published in: IEEE 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
• Language: English
• 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
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/83.877222

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.