Downsampling Based Light Field Video Coding with Restoration Network Using Joint Spatio-Angular and Epipolar Information

Duong, Vinh Van; Huu, Thuc Nguyen; Yim, Jonghoon

doi:10.1109/icip46576.2022.9897948

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…The above experimental results proved the goodness of the designed network. LFSR methods enables downsampling-based light field video compression techniques [22]. In the future, we will apply a more suitable selection mechanism super-resolution network to downsampling-based light field video compression networks.…”

Section: Discussionmentioning

confidence: 99%

Light field image super-resolution using selective kernel convolution

Zhang

Duong²,

Yim³

2023

International Workshop on Advanced Imaging Technology (IWAIT) 2023

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Over the years, many methods have emerged to solve the super-resolution problem of light field images, and among them, those methods based on deep learning are noted quite attractive recently. Although the features extracted from epipolar domain for the super-resolution of light field images are actively investigated due to their potential capability of well capturing the relationship between spatial and angular domains, we note that spatial features are still the most important foundation in feature extraction. In this paper, we design a network, named as LFSelectSR, employing multiple convolutional kernels to fully extract spatial features and introduce a dynamic selection mechanism that can extract the most valuable spatial features. By training and testing the network using well-known datasets, we demonstrate its excellent performance of achieving the level of state-of-the-arts under certain conditions.

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Section: Discussionmentioning

confidence: 99%

Light field image super-resolution using selective kernel convolution

Zhang

Duong²,

Yim³

2023

International Workshop on Advanced Imaging Technology (IWAIT) 2023

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“…With the rapid development of deep learning, deep learning technology has been widely applied to various image processing tasks and has achieved significant success. Inspired by this, some researchers have devoted to studying learning-based light field image compression methods [26][27][28]. The learning-based compression methods can be divided into two categories: using deep learning tools to enhance the traditional light field image compression framework and using deep learning frameworks to perform end-to-end compression of light field images.…”

Section: Learning-based Light Field Image Compressionmentioning

confidence: 99%

End-to-End Light Field Image Compression with Multi-Domain Feature Learning

Ye,

Li,

et al. 2024

Applied Sciences

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Recently, end-to-end light field image compression methods have been explored to improve compression efficiency. However, these methods have difficulty in efficiently utilizing multi-domain features and their correlation, resulting in limited improvement in compression performance. To address this problem, a novel multi-domain feature learning-based light field image compression network (MFLFIC-Net) is proposed to improve compression efficiency. Specifically, an EPI-based angle completion module (E-ACM) is developed to obtain a complete angle feature by fully exploring the angle information with a large disparity contained in the epipolar plane image (EPI) domain. Furthermore, in order to effectively reduce redundant information in the light field image, a spatial-angle joint transform module (SAJTM) is proposed to reduce redundancy by modeling the intrinsic correlation between spatial and angle features. Experimental results demonstrate that MFLFIC-Net achieves superior performance on MS-SSIM and PSNR metrics compared to public state-of-the-art methods.

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Section: Bio-inspired Devices For Efficient Image Acquisitionmentioning

confidence: 99%

“…115 LFC technology is being applied in a variety of new applications, along with technological improvements such as the high resolution image sensors and miniaturization of the imaging system. [116][117][118][119] To mimic a reflecting superposition-type eye, Huang et al integrated an elastomeric polymer and a micro-square tube array surrounding four highly reflective sidewalls to improve light sensitivity. (Fig.…”

Section: High Sensitivity Visionmentioning

confidence: 99%