Robust color correction in stereo vision

Wang, Qi; Yan, Pingkun; Yuan, Yuan; Li, Xuelong

doi:10.1109/icip.2011.6116722

Cited by 18 publications

(12 citation statements)

References 12 publications

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“…To build nonlinear lookup tables, researchers also introduce dynamic programming [17] or polynomial basis [18] optimization by local Gaussian-like analysis in the image space. In [19], the input image is segmented and corrected by locally corresponding keypoints. Shao et al introduce both preferred region selection [20] and linear regression [21] to find the correction coefficients for local regions.…”

Section: Related Workmentioning

confidence: 99%

Spatio-Temporally Consistent Color and Structure Optimization for Multiview Video Color Correction

Ceulemans

Munteanu

et al. 2015

IEEE Trans. Multimedia

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When compared to conventional 2-D video, multiview video can significantly enhance the visual 3-D experience in 3-D applications by offering horizontal parallax. However, when processing images originating from different views, it is common that the colors between the different cameras are not well-calibrated. To solve this problem, a novel energy function-based color correction method for multiview camera setups is proposed to enforce that colors are as close as possible to those in the reference image but also that the overall structural information is well-preserved. The proposed system introduces a spatio-temporal correspondence matching method to ensure that each pixel in the input image gets bijectively mapped to a reference pixel. By combining this mapping with the original structural information, we construct a global optimization algorithm in a Laplacian matrix formulation and solve it using a sparse matrix solver. We further introduce a novel forward-reverse objective evaluation model to overcome the problem of lack of ground truth in this field. The visual comparisons are shown to outperform state-of-the-art multiview color correction methods, while the objective evaluation reports PSNR gains of up to 1.34 dB and SSIM gains of up to 3.2%, respectively.

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Section: Related Workmentioning

confidence: 99%

Spatio-Temporally Consistent Color and Structure Optimization for Multiview Video Color Correction

Ceulemans

Munteanu

et al. 2015

IEEE Trans. Multimedia

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show abstract

“…As shown in Fig. 2e, the result of our colour correction is better than the result of [2] (Fig. 2d ).…”

mentioning

confidence: 76%

“…Employing a local method, Hwang et al [1] and Wang et al [2] used SIFT descriptor matching, but this method only yielded a sparse sampling of corresponding points on an image and could therefore produce biased colour compensating results. Won et al [3] optimised an affine colour correction function that was computed based on local correspondence matching, but this method did not take local features relatively into consideration.…”

mentioning

confidence: 99%

“…Won et al [3] optimised an affine colour correction function that was computed based on local correspondence matching, but this method did not take local features relatively into consideration. Wang et al [2] used mean-SIFT segmentation and corrected the colour region by region factoring in local features. However, the colour distortion characteristics within the segments were not consistent.…”

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confidence: 99%

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Colour correction of stereo images using local correspondence

Lee

2014

Electron. lett.

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A method for enhancing the accuracy of colour correction in stereo images is proposed. The goal is to perform colour compensation at the corresponding points in a stereo image pair using local correspondence information. First, the relevant matching points for colour transfer are extracted using a modified stereo matching algorithm. Then, in order to account for illumination variations and occlusion areas, a new colour transfer method is applied through the weighted sum of the colour difference using local features. The performance of the proposed algorithm has been tested on the reference colourmodified Middlebury dataset.

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“…On the other hand, they usually operate on 4 4 blocks, yielding limited degrees of freedom. Pairwise basis function based methods are suitable to fit various discrete processing units of image segmentation [52] or separated Gaussian model [53] , but accurate video segmentation is still difficult. Moreover, even if with good segmentation results, color compensation on segmented areas or blocks would result in outliers and the subsequent color compensation may introduce blocking artifacts or obvious color gaps between different areas.…”

Section: Multiview Color Correctionmentioning

confidence: 99%

A survey on multiview video synthesis and editing

Zhang

2016

Tinshhua Sci. Technol.

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Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.

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Robust color correction in stereo vision

Cited by 18 publications

References 12 publications

Spatio-Temporally Consistent Color and Structure Optimization for Multiview Video Color Correction

Spatio-Temporally Consistent Color and Structure Optimization for Multiview Video Color Correction

Colour correction of stereo images using local correspondence

A survey on multiview video synthesis and editing

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