Implicit Epipolar Geometric Function based Light Field Continuous Angular Representation

Lin, Zhouchen; Zong, Bo; Wang, Qiming; Yu, Junle; Zhou, Wenhui

doi:10.1109/cvprw59228.2023.00349

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…However, this approach becomes complicated and inefficient when dealing with LF devices containing multiple angular resolutions in one shot/scene [6]. The use of divide‐and‐conquer strategies [7] with an angular‐flexible network [8] can help to improve the situation, but it requires more procedures, requiring the spatial‐angular separable convolution [9] for 2D shot(s) and the 3D convolution [10] for time‐series consideration. These procedures either underutilize all angular information by discarding certain views, or overlook the correlation between LF image SR and different angular resolutions [11].…”

Section: Introductionmentioning

confidence: 99%

Light‐field image super‐resolution with depth feature by multiple‐decouple and fusion module

Chan,

2024

Electronics Letters

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Light‐field (LF) images offer the potential to improve feature capture in live scenes from multiple perspectives, and also generate additional normal vectors for performing super‐resolution (SR) image processing. With the benefit of machine learning, established AI‐based deep CNN models for LF image SR often individualize the models for various resolutions. However, the rigidity of these approaches for actual LF applications stems from the considerable diversity in angular resolution among LF instruments. Therefore, an advanced neural network proposal is required to utilize a CNN‐based model for super‐resolving LF images with different resolutions obtained from provided features. In this work, a preprocessing to calculate the depth channel from given LF information is first presented, and then a multiple‐decouple and fusion module is introduced to integrate the VGGreNet for the LF image SR, which collects global‐to‐local information according to the CNN kernel size and dynamically constructs each view through a global view module. Besides, the generated features are transformed to a uniform space to perform final fusion, achieving global alignment for precise extraction of angular information. Experimental results show that the proposed method can handle benchmark LF datasets with various angular and different resolutions, reporting the effectiveness and potential performance of the method.

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Section: Introductionmentioning

confidence: 99%

Light‐field image super‐resolution with depth feature by multiple‐decouple and fusion module

Chan,

2024

Electronics Letters

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KULF-TT53: A Display-Specific Turntable-Based Light Field Dataset for Subjective Quality Assessment

Javidi,

Martini,

Kara

2023

Electronics

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Light field datasets enable researchers to conduct both objective and subjective quality assessments, which are particularly useful when acquisition equipment or resources are not available. Such datasets may vary in terms of capture technology and methodology, content, quality characteristics (e.g., resolution), and the availability of subjective ratings. When contents of a light field dataset are visualized on a light field display, the display system matches the received input to its output capabilities through various processes, such as interpolation. Therefore, one of the most straightforward methods to create light field contents for a specific display is to consider its visualization parameters during acquisition. In this paper, we introduce a novel display-specific light field dataset, captured using a DSLR camera and a turntable rig. The visual data of the seven static scenes were recorded twice by using two settings of angular resolution. While both were acquired uniformly within a 53-degree angle, which matches the viewing cone of the display they were captured for, one dataset consists of 70 views per content, while the other of 140. Capturing the contents twice was a more straightforward solution than downsampling, as the latter approach could either degrade the quality or make the FOV size inaccurate. The paper provides a detailed characterization of the captured contents, as well as compressed variations of the contents with various codecs, together with the calculated values of commonly-used quality metrics for the compressed light field contents. We expect that this dataset will be useful for the research community working on light field compression, processing, and quality assessment, for instance to perform subjective quality assessment tests on a display with a 53-degree display cone and to test new interpolation methods and objective quality metrics. In future work, we will also focus on subjective tests and provide relevant results. This dataset is made free to access for the research community.

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Implicit Epipolar Geometric Function based Light Field Continuous Angular Representation

Cited by 2 publications

References 31 publications

Light‐field image super‐resolution with depth feature by multiple‐decouple and fusion module

Light‐field image super‐resolution with depth feature by multiple‐decouple and fusion module

KULF-TT53: A Display-Specific Turntable-Based Light Field Dataset for Subjective Quality Assessment

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