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Related Experiment Videos

Multiview image coding using depth layers and an optimized bit allocation.

Andriy Gelman¹, Pier Luigi Dragotti, Vladan Velisavljević

¹Department of Electrical and Electronic Engineering, Imperial College London, London, UK. ag504@imperial.ac.uk

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|June 2, 2012

Summary

This study introduces a new wavelet-based compression algorithm for multiview images using a layer-based approach. The novel method enhances compression efficiency and outperforms existing state-of-the-art codecs.

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Area of Science:

Computer Vision
Image Processing
Signal Processing

Background:

Multiview image compression is crucial for applications like 3D television and virtual reality.
Existing methods face challenges in efficiently representing and compressing complex 3D scenes from multiple viewpoints.

Purpose of the Study:

To develop a novel wavelet-based compression algorithm for multiview images.
To improve the rate-distortion performance of multiview image coding.

Main Methods:

A layer-based representation is used, approximating the 3D scene with depth planes and disparities.
The 3D discrete wavelet transform (DWT), incorporating disparity compensation and shape adaptation, is applied.
Wavelet coefficients and layer contours are quantized and entropy coded, with a bit allocation strategy.

Main Results:

The proposed algorithm achieves superior rate-distortion performance compared to state-of-the-art codecs.
Performance was validated on diverse datasets with varying complexity.
The layer-based approach effectively captures 3D scene information.

Conclusions:

The novel wavelet-based compression algorithm offers significant improvements for multiview image coding.
The proposed method provides an efficient solution for compressing complex 3D visual data.
This technique has the potential to enhance immersive media experiences.