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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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Context coding of depth map images under the piecewise-constant image model representation.

Ioan Tabus, Ionut Schiopu, Jaakko Astola

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |June 29, 2013
    PubMed
    Summary

    This study presents a novel lossless compression method for depth maps by representing them as crack-edges, constant depth regions, and region depth values. This efficient technique achieves significant compression ratios for depth image compression.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Data Compression

    Background:

    • Depth map images contain unique redundancies not fully exploited by standard image compression techniques.
    • Existing methods for lossless compression often struggle with the specific characteristics of depth data.

    Purpose of the Study:

    • To develop an efficient lossless compression method specifically tailored for depth map images.
    • To leverage the structural properties of depth images for improved compression performance.

    Main Methods:

    • Representing depth images using crack-edges, constant depth regions, and depth values within regions.
    • Employing 2D context coding with pruned context trees for crack-edge transmission.
    • Encoding region depth values based on neighboring regions to exploit depth smoothness.

    Main Results:

    • Achieved significant lossless compression ratios for depth images, ranging from 10 to 65 times.
    • The method effectively reconstructs constant depth regions from transmitted crack-edge data.
    • Demonstrated suitability as an entropy coding stage for lossy depth compression.

    Conclusions:

    • The proposed piecewise-constant image model coding with advanced techniques offers superior lossless compression for depth maps.
    • The method efficiently exploits depth image redundancies, leading to high compression rates.
    • This approach provides a versatile tool for both lossless and lossy depth data compression.