Selective hole-filling for depth-image based rendering

Oliveira, Adriano Q. de; Fickel, Guilherme P.; Walter, Marcelo; Jung, Cláudio Rosito

doi:10.1109/icassp.2015.7178157

Cited by 22 publications

(11 citation statements)

References 10 publications

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“…In this section, subjective evaluation and objective evaluation are compared among the proposed and previous methods, including Criminisi's exemplar-based image inpainting method [14], Daribo's depth-aided inpainting method [15], divide-and-conquer hole-filling method [12], Oliveira's inpainting-based method [16], and Kao's disocclusions filling method [17]. In References [12,14,16,17], and the proposed method, the virtual view synthesis needs only a single reference image and its depth image, while the method in Reference [15] is under the assumption that the depth image of the virtual view is given.…”

Section: Resultsmentioning

confidence: 99%

“…For the complex background texture, the edge structure may be distorted which affects the visual quality. In Oliveira's method [16], the priority consists of the confidence term and the depth term. While the hole filling starts from the background side, the lack of the data term makes the structure and texture difficult to maintain effectively, as shown in Figure 11e.…”

Section: Resultsmentioning

confidence: 99%

“…The patch with lower depth variance is given higher priority and filled by the patch in the source region, which has similar depth levels and colors. Oliveira et al [16] replace the data term with the depth term, which prioritizes the greatest depth values. Kao [17] proposes a depth-based gray-level distance to measure the similarity between the two patches.…”

Section: Related Workmentioning

confidence: 99%

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Artifact Handling Based on Depth Image for View Synthesis

Chen

Liang

et al. 2019

Applied Sciences

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The depth image based rendering (DIBR) is a popular technology for 3D video and free viewpoint video (FVV) synthesis, by which numerous virtual views can be generated from a single reference view and its depth image. However, some artifacts are produced in the DIBR process and reduce the visual quality of virtual view. Due to the diversity of artifacts, effectively handling them becomes a challenging task. In this paper, an artifact handling method based on depth image is proposed. The reference image and its depth image are extended to fill the holes that belong to the out-of-field regions. A depth image preprocessing method is applied to project the ghosts to their correct place. The 3D warping process is optimized by an adaptive one-to-four method to deal with the cracks and pixel overlapping. For disocclusions, we calculate depth and background terms of the filling priority based on depth information. The search for the best matching patch is performed simultaneously in the reference image and the virtual image. Moreover, adaptive patch size is used in all hole-filling processes. Experimental results demonstrate the effectiveness of the proposed method, which has better performance compared with previous methods in subjective and objective evaluation.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Artifact Handling Based on Depth Image for View Synthesis

Chen

Liang

et al. 2019

Applied Sciences

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“…There are different techniques of image inpainting [2][3][4][12][13][19][20][21]23,35] existing in literature. Mainly they can be classified into Texture Synthesis Inpainting, PDE Inpainting, Exemplar Inpainting, Hybrid Inpainting and Fast semiautomatic inpainting.…”

Section: Related Workmentioning

confidence: 99%

Improved Exemplar based Image Inpainting for Partial Instance Occlusion Handling with K-means Clustering and YCbCr Color Space

Abin¹,

Thepade²

2021

IJACSA

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The images acquired in real time outdoor environment are often subject to uneven illumination conditions, cloudy weather, lighting conditions. The instances of partial occlusions deteriorate the background modeling of such scenes. Varying illumination outdoor scene set of images with partial occlusions are addressed through this investigative work. There is a need for a restoration method that finds improved subjective perception and execution time. The proposed work focuses on novel amended exemplar model to improve the subjective perception. The exemplar inpainting method is improved through the color quantization with K-means clustering approach in YCbCr color space. Experimental validations and proposed method results show better improvement in qualitative and objective measures than existing methods. The average "Peak Signal to Noise Ratio (PSNR)" as 28.2869 and "Structural SIMilarity index (SSIM)" as 0.9759 of the proposed method has shown better results respectively both visually and with a tradeoff in time.

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“…By comparing the similarity with the image-depth patches, different levels of enhancements are utilised to enhance the visual quality of the image, as well as the sharpness of the depth map. The method does not require complicated training parameters and is suitable for practical depth-based image rendering applications [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Precise depth map upsampling and enhancement based on edge‐preserving fusion filters

Chang

Yang

2018

IET Computer Vision

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A texture image plus its associated depth map is the simplest representation of a three-dimensional image and video signals and can be further encoded for effective transmission. Since it contains fewer variations, a depth map can be coded with much lower resolution than a texture image. Furthermore, the resolution of depth capture devices is usually also lower. Thus, a low-resolution depth map with possible noise requires appropriate interpolation to restore it to full resolution and remove noise. In this study, the authors propose potency guided upsampling and adaptive gradient fusion filters to enhance the erroneous depth maps. The proposed depth map enhancement system can successfully suppress noise, fill missing values, sharpen foreground objects, and smooth background regions simultaneously. Their experimental results show that the proposed methods perform better in terms of both visual and subjective metrics than the classic methods and achieve results that are visually comparable with those of some time-consuming methods.

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Selective hole-filling for depth-image based rendering

Cited by 22 publications

References 10 publications

Artifact Handling Based on Depth Image for View Synthesis

Artifact Handling Based on Depth Image for View Synthesis

Improved Exemplar based Image Inpainting for Partial Instance Occlusion Handling with K-means Clustering and YCbCr Color Space

Precise depth map upsampling and enhancement based on edge‐preserving fusion filters

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