A novel rate-control for predictive image coding with constant quality

Joan Bartrina-Rapesta, Michael W. Marcellin, Joan Serra-Sagristá, Miguel Hernàndez-Cabronero

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Predictive image coding systems yield a high-compression performance at low computational complexity, and are therefore popular in standards and prominent coding techniques for both lossless and near-lossless compression. However, few prediction-based coding techniques include rate-control approaches because of the difficulty in properly combining the prediction feedback loop and the quantization. None of the rate-control approaches for predictive image coding are focused on delivering homogeneous quality along the whole image. The main objective of this paper is to define a novel rate-control approach based on prediction that homogenises the quality over the entire image. The extensive experimental results, on medical, remote sensing, and natural images, suggest that our proposal attains more regular image quality and lower peak absolute error than the state-of-the-art approaches based on prediction and also transform-based techniques such as JPEG2000 and CCSDS-122.

Original languageEnglish (US)
Article number2931442
Pages (from-to)103918-103930
Number of pages13
JournalIEEE Access
StatePublished - 2019


  • Constant-quality lossy compression
  • Prediction-based image coding
  • Rate-control

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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