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A low-complexity image compression approach with single spatial prediction mode and transform

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Abstract

The well-known low-complexity JPEG and the newer JPEG-XR systems are based on block-based transform and simple transform-domain coefficient prediction algorithms. Higher complexity image compression algorithms, obtainable from intra-frame coding tools of video coders H.264 or HEVC, are based on multiple block-based spatial-domain prediction modes and transforms. This paper explores an alternative low-complexity image compression approach based on a single spatial-domain prediction mode and transform, which are designed based on a global image model. In our experiments, the proposed single-mode approach uses an average 20.5 % lower bit-rate than a standard low-complexity single-mode image coder that uses only conventional DC spatial prediction and 2-D DCT. It also does not suffer from blocking effects at low bit-rates.

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Notes

  1. JPEG-XR and Kodak test images were converted to YCbCr format with 420 sampling for the experiments.

  2. A Larger \(\rho \) value would model smoother blocks and a smaller \(\rho \) value detailed blocks better.

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Authors and Affiliations

  1. Middle East Technical University, Ankara, Turkey

    Fatih Kamisli

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  1. Fatih Kamisli
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Correspondence to Fatih Kamisli.

Additional information

This research was supported by Grant 113E516 of TÜBİTAK.

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Kamisli, F. A low-complexity image compression approach with single spatial prediction mode and transform. SIViP 10, 1409–1416 (2016). https://doi.org/10.1007/s11760-016-0908-3

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  • DOI: https://doi.org/10.1007/s11760-016-0908-3

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