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A comparison of fast inverse discrete cosine transform algorithms

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Abstract

The discrete cosine transform (DCT) is often applied to image compression to decorrelate picture data before quantization. This decorrelation results in many of the quantized transform coefficients equaling zero, hence the compression gain. At the decoder, very few nonzero quantized transform coefficients are received, so the input to the inverse DCT is sparse, greatly reducing the required computation. This paper describes different styles of implementations of fast inverse DCTs designed especially for sparse data and compares them on workstation processors.

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Authors and Affiliations

  1. Computer Systems Laboratory, Stanford University, 94305, Stanford, CA, USA

    Andy C. Hung & Teresa H. -Y. Meng

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  1. Andy C. Hung
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  2. Teresa H. -Y. Meng
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Correspondence to Andy C. Hung.

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This research has been sponsored by ARPA

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Hung, A.C., Meng, T.H.Y. A comparison of fast inverse discrete cosine transform algorithms. Multimedia Systems 2, 204–217 (1994). https://doi.org/10.1007/BF01215398

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