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Related Experiment Videos

Arbitrary-ratio image resizing using fast DCT of composite length for DCT-based transcoder.

Young Seo Park1, Hyun Wook Park

  • 1Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Korea. young@athena.kaist.ac.kr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 17, 2006
PubMed
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This study introduces a fast image resizing method for compressed images. It efficiently adjusts image size in the Discrete Cosine Transform (DCT) domain, offering better quality and speed than existing techniques.

Area of Science:

  • Digital Image Processing
  • Signal Processing
  • Computer Vision

Background:

  • Image transcoding often requires resizing, which can degrade quality or be computationally expensive.
  • Existing methods for image resizing in the Discrete Cosine Transform (DCT) domain have limitations in speed and efficiency.
  • Spatial-domain resizing methods can be slow and may not preserve compression-related information effectively.

Purpose of the Study:

  • To develop a fast and efficient arbitrary-ratio image resizing method for compressed images.
  • To perform image resizing directly in the DCT domain, minimizing data conversion and information loss.
  • To improve upon existing DCT-domain resizing techniques in terms of speed and Peak Signal-to-Noise Ratio (PSNR).

Main Methods:

  • The proposed method utilizes a fast inverse and forward Discrete Cosine Transform (DCT) of composite length.

Related Experiment Videos

  • Image downsizing is achieved by truncating high-frequency DCT coefficients.
  • Image upsizing is performed by padding zero coefficients to the high-frequency components in the DCT domain.

    • Main Results:

    • The method enables arbitrary-ratio image resizing with reduced computational complexity.
    • It achieves a good Peak Signal-to-Noise Ratio (PSNR), indicating high image quality preservation.
    • The proposed DCT-domain approach outperforms both spatial-domain and previous DCT-domain resizing methods.

    Conclusions:

    • The developed fast DCT-domain image resizing method is efficient for transcoding compressed images.
    • It offers a favorable trade-off between computational complexity and image quality.
    • This technique provides a significant improvement for applications requiring rapid and high-quality image size adjustment.