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Updated: May 16, 2026

A New Workflow for Sampling and Digitizing Increment Cores
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A New Workflow for Sampling and Digitizing Increment Cores

Published on: September 27, 2024

Modifying JPEG binary arithmetic codec for exploiting inter/intra-block and DCT coefficient sign redundancies.

Gopal Lakhani1

  • 1Department of Computer Science, Texas Tech University, Lubbock, TX 79409, USA. gopal.lakhani@ttu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|November 30, 2012
PubMed
Summary
This summary is machine-generated.

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This study enhances JPEG arithmetic coding (JAC) with four novel prediction techniques, significantly improving image compression efficiency. The modified JAC algorithm achieves substantial code reduction compared to standard JPEG and rivals JPEG XR performance.

Area of Science:

  • Digital image processing
  • Data compression algorithms
  • Information theory

Background:

  • JPEG arithmetic coding (JAC) is a widely used image compression standard.
  • Existing block-based approaches like JPEG introduce inter/intra-block redundancy.
  • JPEG XR represents the latest advancement in block-based image coding.

Purpose of the Study:

  • To introduce and evaluate four novel prediction-based modifications to the JPEG arithmetic coding (JAC) algorithm.
  • To compare the compression performance of the modified JAC against JPEG XR.
  • To address limitations in existing JAC by reducing redundancy and improving coding efficiency.

Main Methods:

  • Developed four prediction coding strategies to exploit inter/intra-block redundancy in block-based image coding.

Related Experiment Videos

Last Updated: May 16, 2026

A New Workflow for Sampling and Digitizing Increment Cores
07:05

A New Workflow for Sampling and Digitizing Increment Cores

Published on: September 27, 2024

  • Modified JAC by altering DC difference coding, DCT coefficient bit significance testing order, sign prediction for DCT coefficients, and end-of-block coding.
  • Conducted experiments on two sets of eight-bit grayscale images (classical test images and large images).
  • Compared performance against JPEG XR (JXR0 and JXR1 configurations).

    • Main Results:

    • Modified JAC achieved significant code size reduction: 8.9-10.6% for JAC code size and 16.3-23.4% for JPEG Huffman code size on average.
    • For finest quality rate coding, modified JAC outperformed JXR1 by 5.8% and JXR0 by 6.7% on average for large images.
    • Rate-distortion plots indicated modified JAC distinctly outperformed JXR0, with performance comparable to JXR1 in lossy coding.

    Conclusions:

    • The proposed prediction-based modifications substantially enhance JPEG arithmetic coding efficiency without introducing loss.
    • Modified JAC offers competitive or superior compression performance compared to JPEG XR, especially at higher quality settings.
    • This work demonstrates the potential of prediction coding to overcome limitations in block-based image compression standards.