Web of Science

記述言語：英語   出版者・発行元：IEICE Transactions on Information and Systems  

A light field (LF), which is represented as a set of dense, multi-view images, has been used in various 3D applications. To make LF acquisition more efficient, researchers have investigated compressive sensing methods by incorporating certain coding functionalities into a camera. In this paper, we focus on a challenging case called snapshot compressive LF imaging, in which an entire LF is reconstructed from only a single acquired image. To embed a large amount of LF information in a single image, we consider two promising methods based on rapid optical control during a single exposure: time-multiplexed coded aperture (TMCA) and coded focal stack (CFS), which were proposed individually in previous works. Both TMCA and CFS can be interpreted in a unified manner as extensions of the coded aperture (CA) and focal stack (FS) methods, respectively. By developing a unified algorithm pipeline for TMCA and CFS, based on deep neural networks, we evaluated their performance with respect to other possible imaging methods. We found that both TMCA and CFS can achieve better reconstruction quality than the other snapshot methods, and they also perform reasonably well compared to methods using multiple acquired images. To our knowledge, we are the first to present an overall discussion of TMCA and CFS and to compare and validate their effectiveness in the context of compressive LF imaging.

DOI： 10.1587/transinf.2022PCP0003

Web of Science

Scopus

CiNii Research

記述言語：英語   出版者・発行元：IEICE Transactions on Information and Systems  

Inspired by the framework of algorithm unrolling, we propose a scalable network architecture that computes layer patterns for light field displays, enabling control of the trade-off between the display quality and the computational cost on a single pre-trained network.

DOI： 10.1587/transinf.2022PCL0002

Web of Science

Scopus

CiNii Research

出版者・発行元：Optics Express  

Integral three-dimensional (3D) displays can display naturally viewable 3D images. However, displaying 3D images with high pixel density is difficult because the maximum pixel number is restricted by the number of lenses of a lens array. Therefore, we propose a method for increasing the maximum pixel density of 3D images by optically synthesizing the displayed images of an integral 3D display and high-definition two-dimensional display using a half mirror. We evaluated the improvements in 3D image resolution characteristics through simulation analysis of the modulation transfer function. We developed a prototype display system that can display 3D images with a maximum resolution of 4K and demonstrated the effectiveness of the proposed method.

DOI： 10.1364/OE.469045

Web of Science

Scopus

出版者・発行元：Signal Processing: Image Communication  

Short-time discrete Fourier transform (ST-DFT) is known as a promising technique for image and video denoising. The seminal work by Saito and Komatsu hypothesized that natural video sequences can be represented by sparse ST-DFT coefficients and noisy video sequences can be denoised on the basis of statistical modeling and shrinkage of the ST-DFT coefficients. Motivated by their theory, we develop an application of ST-DFT for denoising multi-view images. We first show that multi-view images have sparse ST-DFT coefficients as well and then propose a new statistical model, which we call the multi-block Laplacian model, based on the block-wise sparsity of ST-DFT coefficients. We finally utilize this model to carry out denoising by solving a convex optimization problem, referred to as the least absolute shrinkage and selection operator. A closed-form solution can be computed by soft thresholding, and the optimal threshold value is derived by minimizing the error function in the ST-DFT domain. We demonstrate through experiments the effectiveness of our denoising method compared with several previous denoising techniques. Our method implemented in Python language is available from https://github.com/ctsutake/mviden.

DOI： 10.1016/j.image.2022.116710

Web of Science

Scopus

出版者・発行元：Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition  

We propose a method for compressively acquiring a dynamic light field (a 5-D volume) through a single-shot coded image (a 2-D measurement). We designed an imaging model that synchronously applies aperture coding and pixel-wise exposure coding within a single exposure time. This coding scheme enables us to effectively embed the original information into a single observed image. The observed image is then fed to a convolutional neural network (CNN) for light-field reconstruction, which is jointly trained with the camera-side coding patterns. We also developed a hardware prototype to capture a real 3-D scene moving over time. We succeeded in acquiring a dynamic light field with 5x5 viewpoints over 4 temporal sub-frames (100 views in total)from a single observed image. Repeating capture and reconstruction processes over time, we can acquire a dynamic light field at 4x the frame rate of the camera. To our knowledge, our method is the first to achieve a finer temporal resolution than the camera itself in compressive light-field acquisition. Our software is available from our project webpage.11https://www.fujii.nuee.nagoya-u.ac.jp/Research/CompCam2

DOI： 10.1109/CVPR52688.2022.01921

Web of Science

Scopus

Web of Science

出版者・発行元：Proceedings of the International Display Workshops  

We propose a method of displaying two different 3D scenes on a single layered light-field display, where the layer patterns are optimized for the two scenes simultaneously. We demonstrate that both scenes can be displayed in high quality when the viewing zones for them are separated sufficiently.

Scopus

出版者・発行元：Proceedings of the International Display Workshops  

We propose an image generation method to display three-dimensional (3D) images with high maximum pixel density and improved subjective quality on a two-dimensional image synthetic integral 3D display. In addition to the target light field image, weight maps obtained from the depth information were used to generate the images.

Scopus

出版者・発行元：Proceedings - International Conference on Image Processing, ICIP  

Compression of the sign information of discrete cosine transform coefficients is an intractable problem in image compression schemes due to the equiprobable occurrence of the sign bits. To overcome this difficulty, we propose an efficient compression method for such sign information based on phase retrieval, which is a classical signal restoration problem attempting to find the phase information of discrete Fourier transform coefficients from their magnitudes. In our compression strategy, the sign bits of all the AC components in the cosine domain are excluded from a bitstream at the encoder and are complemented at the decoder by solving a sign recovery problem, which we call sign retrieval. The experimental results demonstrate that the proposed method outperforms previous techniques for sign compression in terms of a rate-distortion criterion. Our method implemented in Python language is available from https://github.com/ctsutake/sr.

DOI： 10.1109/ICIP42928.2021.9506155

Web of Science

Scopus

出版者・発行元：Proceedings - International Conference on Image Processing, ICIP  

A light field (LF), which is represented as a set of dense multiview images, has been utilized in various 3D applications. To make LF acquisition more efficient, researchers have investigated compressive sensing methods by incorporating modulation or coding functions into the camera. In this work, we investigate a challenging case of compressive LF acquisition in which an entire LF should be reconstructed from only a single coded image. To achieve this goal, we propose a new modulation scheme called factorized modulation that can approximate arbitrary 4D modulation patterns in a factorized manner. Our method can be hardwareimplemented by combining the architectures for coded aperture and pixelwise coded exposure imaging. The modulation pattern is jointly optimized with a CNNbased reconstruction algorithm. Our method is validated through extensive evaluations against other modulation schemes.

DOI： 10.1109/ICIP42928.2021.9506797

Web of Science

Scopus

出版者・発行元：Proceedings - International Conference on Image Processing, ICIP  

Over the past decade, nonlinear image compression techniques based on neural networks have been rapidly developed to achieve more efficient storage and transmission of images compared with conventional linear techniques. A typical nonlinear technique is implemented as a neural network trained on a vast set of images, and the latent representation of a target image is transmitted. In contrast to the previous nonlinear techniques, we propose a new image compression method in which a neural network model is trained exclusively on a single target image, rather than a set of images. Such an overfitting strategy enables us to embed fine image features in not only the latent representation but also the network parameters, which helps reduce the reconstruction error against the target image. The effectiveness of our method is validated through a comparison with conventional image compression techniques in terms of a rate-distortion criterion.

DOI： 10.1109/ICIP42928.2021.9506367

Web of Science

Scopus

出版者・発行元：Proceedings of SPIE - The International Society for Optical Engineering  

This paper attempts to improve denoising efficiency of BM3D technique for videos, i.e., VBM3D. VBM3D constructs 3D cubes from target video frames by a block matching algorithm that minimizes the residual matching error. However, such a cube formation results in sacrificing the pixel correlation in the temporal direction. This paper thus modifies this step to preserve the sub-pixel alignment, which makes the Fourier coefficients of each cube located on a vicinity of a certain plane in the 3-D Fourier domain. Then, SURE-shrinkage technique is separately applied to the inside and outside of the vicinity of the plane to denoise each cube. The experimental results given in this paper demonstrate the validity of our approach.

DOI： 10.1117/12.2591104

Web of Science

Scopus

担当区分：筆頭著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）  

DOI： 10.3169/itej.74.198

記述言語：英語   掲載種別：研究論文（学術雑誌）  

DOI： 10.1109/access.2019.2913024

担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）  

DOI： 10.1587/transinf.2017EDP7201

担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）  

DOI： 10.1587/transinf.2015EDP7244