The Fast Hartley Transform Algorithm
IEEE Transactions on Computers
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete cosine transform filtering
Signal Processing
IEEE Transactions on Computers
A Storage Efficient Way to Implement the Discrete Cosine Transform
IEEE Transactions on Computers
Fast Algorithms for the 2-D Discrete Cosine Transform
IEEE Transactions on Computers
On Computing the Discrete Cosine Transform
IEEE Transactions on Computers
The effects of a visual fidelity criterion of the encoding of images
IEEE Transactions on Information Theory
A Discrete Fourier-Cosine Transform Chip
IEEE Journal on Selected Areas in Communications
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
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Among the various image data compression methods, the discrete cosine transform (DCT) has emerged as a popular method in gray-scale image compression. This paper presents detailed analyses of several interesting properties of the DCT, which can be described in three parts: the frequency characteristics, the filtering properties, and the subband properties. These analyses provide insights into the following topics: (1) the frequency distribution of the DCT in terms of the Fourier transform components, (2) the filtering characteristics of the DCT, and (3) the use of the DCT as subband filters. Surprisingly, based on our analyses, the DCT behaves very much like subband filters, with potential applications not only to image data compression but also to image analysis. The formulas presented in this paper have been checked for correctness by computer simulations, and applications to image data compression have been demonstrated with simulation results.