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Related Experiment Videos

Radiological image compression using full-frame cosine transform with adaptive bit-allocation.

K K Chan1, S L Lou, H K Huang

  • 1Department of Radiological Sciences, University of California, Los Angeles 90024.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|March 1, 1989
PubMed
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A novel bit-allocation scheme enhances radiological image compression using a full-frame cosine transform. This method improves high-frequency component handling, faithfully reproducing sharp edges with minimal degradation at compression ratios below 10:1.

Area of Science:

  • Medical Imaging
  • Image Processing
  • Computer Vision

Background:

  • Radiological image compression is crucial for efficient storage and transmission.
  • Existing methods may introduce artifacts, particularly around high-contrast edges.
  • Full-frame cosine transform is a common technique in image compression.

Purpose of the Study:

  • To introduce a new bit-allocation scheme for radiological image compression.
  • To improve the handling of high-frequency components in the transform domain.
  • To eliminate artifacts and enhance image quality at high compression ratios.

Main Methods:

  • A new bit-allocation scheme based on the full-frame cosine transform.
  • Utilized a two-dimensional bit-allocation table for encoding compression data.

Related Experiment Videos

  • Tested on 10 radiological chest images.

    • Main Results:

    • The new scheme effectively handles high-frequency components.
    • Faithful reproduction of high-contrast sharp edges was achieved.
    • No perceivable degradation was observed at compression ratios below 10:1.
    • Eliminated previously reported artifacts associated with sharp edges.
    • Image quality was comparable or superior to the previous method.

    Conclusions:

    • The new bit-allocation scheme offers superior performance in radiological image compression.
    • It preserves image fidelity, especially around critical features like sharp edges.
    • The algorithm is suitable for simple and fast hardware implementation.