Analysis of maximum tolerant depth distortion in view synthesis

Wang, Laihua; Hou, Chunping; Qi, Sumin; Jiang, Lanlan

doi:10.1007/s11042-017-4690-1

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…However, imperfect holes filling methods may introduce some new types of distortions or artifacts, such as strip distortion and occluded distortion. These distortions are quite different from the traditional distortions [4].…”

Section: Introductionmentioning

confidence: 72%

Quality Assessment for DIBR-Synthesized Images With Local and Global Distortions

Wang

Zhao

et al. 2020

IEEE Access

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Depth-Image-Based-Rendering (DIBR), as one important technique in 3D video system, can be used to generate virtual views. Unfortunately, the DIBR algorithms will introduce various distortions and induce an annoying viewing experience. And it has been proved that traditional 2D assessment quality metrics are not suitable for the DIBR-synthesized views. In this paper, we propose a novel approach to assess the quality of DIBR-synthesized images. The proposed method mainly considers three kinds of DIBR-related distortions: holes distortion, strip-sharped distortion and global sharpness. Holes and strip distortions as two local features are used to characterize the local quality of DIBR-synthesized image, respectively. For the global sharpness we consider the Just Notice Difference (JND) model of human eyes and use it to extract the JND-based global difference for analyzing the global quality. Finally, we combine the holes distortion evaluation, strip distortion evaluation and global quality to infer the overall perceptual quality. Extensive experiments indicate that our method achieves higher accuracy of quality prediction than most competing metrics. INDEX TERMS DIBR, synthesis distortions, quality evaluation, view synthesis, perceptual quality.

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Section: Introductionmentioning

confidence: 72%

Quality Assessment for DIBR-Synthesized Images With Local and Global Distortions

Wang

Zhao

et al. 2020

IEEE Access

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“…In recent years, stereoscopic multi-view video has developed rapidly and occupied an important position not only in 2Dto-3D video conversion system but also in free viewpoint TV (FTV) [1], [2]. Stereoscopic multi-view video gives the audience an immersive experience and allows viewers to experience the beauty of the world [3].…”

Section: Introductionmentioning

confidence: 99%

Quality Evaluation of DIBR-Synthesized Images Based on Holes and Expanded Regions

Zhao

Wang

et al. 2020

IEEE Access

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With the Depth-image-based rendering (DIBR) technique, virtual views can be drawn at any position between two reference viewpoints. However, DIBR algorithm may introduce various distortions in the synthesized images, such as holes, artifact, and stretching. This paper proposes a quality evaluation method for DIBR-synthesized images by analyzing the holes and expanded regions. First, the holes regions are obtained with the watershed algorithm and used to evaluate the quality of the DIBR-synthesized images. Then, the synthesized image is compared with the reference image in the sub-channel, and the number of different pixel values is used to assess the global quality of synthesized images. Finally, the two measures are pooled to calculate the overall quality score of the DIBR synthesized image. Experimental results show that our scheme can better predict the image quality and performs better in terms of implementation time compared with other schemes. INDEX TERMS DIBR, synthesized image, quality evaluation, watershed algorithm, expanded regions.

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Kernel-Ridge Regression-Based Quality Measure and Enhancement of Three-Dimensional-Synthesized Images

Jakhetiya

Jaiswal³

et al. 2021

IEEE Trans. Ind. Electron.

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Analysis of maximum tolerant depth distortion in view synthesis

Cited by 4 publications

References 15 publications

Quality Assessment for DIBR-Synthesized Images With Local and Global Distortions

Quality Assessment for DIBR-Synthesized Images With Local and Global Distortions

Quality Evaluation of DIBR-Synthesized Images Based on Holes and Expanded Regions

Kernel-Ridge Regression-Based Quality Measure and Enhancement of Three-Dimensional-Synthesized Images

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