Abstract

Several depth image-based rendering (DIBR) watermarking methods have been proposed, but they have various drawbacks, such as non-blindness, low imperceptibility and vulnerability to signal or geometric distortion. This paper proposes a template-based DIBR watermarking method that overcomes the drawbacks of previous methods. The proposed method exploits two properties to resist DIBR attacks: the pixel is only moved horizontally by DIBR, and the smaller block is not distorted by DIBR. The one-dimensional (1D) discrete cosine transform (DCT) and curvelet domains are adopted to utilize these two properties. A template is inserted in the curvelet domain to restore the synchronization error caused by geometric distortion. A watermark is inserted in the 1D DCT domain to insert and detect a message from the DIBR image. Experimental results of the proposed method show high imperceptibility and robustness to various attacks, such as signal and geometric distortions. The proposed method is also robust to DIBR distortion and DIBR configuration adjustment, such as depth image preprocessing and baseline distance adjustment.

Highlights

  • Three-dimensional (3D) content has been steadily increasing in popularity because of its excellent lifelike appearance

  • The proposed method was compared with other blind depth-image-based rendering (DIBR) image watermarking systems, Lin’s method [18] and Kim’s method [20]

  • Due to the advent of new 3D applications, DIBR has taken on an important role in 3D content

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Summary

Introduction

Three-dimensional (3D) content has been steadily increasing in popularity because of its excellent lifelike appearance. DIBR consists of three steps: depth image preprocessing, pixel location warping and hole-filling. The first step, improves the quality of the rendered image by reducing the number of holes [32,33,34]. When the viewpoint is moved by the DIBR, an area where no pixel information exists is generated. These areas, referred to as holes, are the main cause of 3D image quality degradation. The image quality can be improved by reducing the number of holes through depth image smoothing

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