Intelligent reversible watermarking and authentication: Hiding depth map information for 3D cameras

Khan, Asifullah; Malik, Sana; Ali, Asad; Chamlawi, Rafiullah; Hussain, M.; Mahmood, Muhammad Tariq; Usman, Imran

doi:10.1016/j.ins.2012.06.014

Cited by 35 publications

(6 citation statements)

References 45 publications

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“…Recently, the rapid technological developments of 3D image and video processing have led to an explosion in demand for 3D content [20] . 3D can bring consumers stereo perception and immersive viewing experiences, and can be displayed not only in movie theaters, but also on home electronics, e.g., television, smartphones, and tablets.…”

Section: Introductionmentioning

confidence: 99%

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

Yang

Wang

et al. 2017

Information Sciences

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Most of the existing 3D video quality assessment (3D-VQA/SVQA) methods only consider spatial information by directly using an image quality evaluation method. In addition, a few take the motion information of adjacent frames into consideration. In practice, one may assume that a single data-view is unlikely to be sufficient for effectively learning the video quality. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose an effective multiview feature learning metric for blind stereoscopic video quality assessment (BSVQA), which jointly focuses on spatial information, temporal information and inter-frame spatio-temporal information. In our study, a set of local binary patterns (LBP) statistical features extracted from a computed frame curvelet representation are used as spatial and spatio-temporal description, and the local flow statistical features based on the estimation of optical flow are used to describe the temporal distortion. Subsequently, a support vector regression (SVR) is utilized to map the feature vectors of each single view to subjective quality scores. Finally, the scores of multiple views are pooled into the final score according to their contribution rate. Experimental results demonstrate that the proposed metric significantly outperforms the existing metrics and can achieve higher consistency with subjective quality assessment.

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Section: Introductionmentioning

confidence: 99%

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

Yang

Wang

et al. 2017

Information Sciences

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“…To this end, the depth image is first converted to a bitstream and then embedded in the wavelet [20] and DCT [35] transformed coefficients. However, the transform domain lossless data hiding techniques have the aforementioned disadvantages, i.e., degraded quality of decoded image and increased length of bitstream.…”

Section: Introductionmentioning

confidence: 99%

“…However, the transform domain lossless data hiding techniques have the aforementioned disadvantages, i.e., degraded quality of decoded image and increased length of bitstream. More importantly, conventional techniques [20,35] do not carefully consider inherent similarities between the color and depth images when generating information bits from the depth image.…”

Section: Introductionmentioning

confidence: 99%

Lossless embedding of depth hints in JPEG compressed color images

Jung

2016

Signal Processing

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“…Image forgery detection techniques can be classified into two categories: active methods and passive methods. Active methods such as watermarking [1] and illegal image copy detection [2][3][4] depend on prior information about the original image. However, in many situations, prior information regarding an image is not available.…”

Section: Introductionmentioning

confidence: 99%

A proposed accelerated image copy-move forgery detection

Fadl

Semary

2014

2014 IEEE Visual Communications and Image Processing Conference

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Image forgery detection is currently one of the interested research fields of image processing. Copy-Move (CM) forgery is one of the frequently used techniques. In this paper, we propose a method which is efficient and fast for detect copy-move regions. The proposed method accelerates block matching strategy. Firstly, the image is divided into fixed-size overlapping blocks then discrete cosine transform is applied to each block to represent its features. Fast k-means clustering technique is used to cluster the blocks into different classes. Zigzag scanning is performed to reduce the length of each block feature vector. The feature vectors of each cluster blocks are lexicographically sorted by radix sort. correlation between each nearby blocks indicates their similarity. The experimental results demonstrate that the proposed method can detect the duplicated regions efficiently, and reduce processing time up to 50% of other previous works.

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Intelligent reversible watermarking and authentication: Hiding depth map information for 3D cameras

Cited by 35 publications

References 45 publications

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain

Lossless embedding of depth hints in JPEG compressed color images

A proposed accelerated image copy-move forgery detection

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