Coded aperture projection

Grosse, Max; Wetzstein, Gordon; Grundhöfer, Anselm; Bimber, Oliver

doi:10.1145/1805964.1805966

Cited by 44 publications

(5 citation statements)

References 30 publications

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“…The above idea of restoring an image by optical convolution is similar to previous work for extending projector depth-of-field [17] and a 2D code using a blur of pattern light [16], but the tasks are different. Idea 2: Physics-in-the-loop (PITL) optimization for designing key aperture and perturbation patterns.…”

Section: Key Ideasmentioning

confidence: 97%

A Coded Aperture as a Key for Information Hiding Designed by Physics-in-the-Loop Optimization

MINAMATA,

HAMASAKI,

KAWASAKI

et al. 2024

IEICE Trans. Inf. & Syst.

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This paper proposes a novel application of coded apertures (CAs) for visual information hiding. CA is one of the representative computational photography techniques, in which a patterned mask is attached to a camera as an alternative to a conventional circular aperture. With image processing in the post-processing phase, various functions such as omnifocal image capturing and depth estimation can be performed. In general, a watermark embedded as high-frequency components is difficult to extract if captured outside the focal length, and defocus blur occurs. Installation of a CA into the camera is a simple solution to mitigate the difficulty, and several attempts are conducted to make a better design for stable extraction. On the contrary, our motivation is to design a specific CA as well as an information hiding scheme; the secret information can only be decoded if an image with hidden information is captured with the key aperture at a certain distance outside the focus range. The proposed technique designs the key aperture patterns and information hiding scheme through evolutionary multi-objective optimization so as to minimize the decryption error of a hidden image when using the key aperture while minimizing the accuracy when using other apertures. During the optimization process, solution candidates, i.e., key aperture patterns and information hiding schemes, are evaluated on actual devices to account for disturbances that cannot be considered in optical simulations. Experimental results have shown that decoding can be performed with the designed key aperture and similar ones, that decrypted image quality deteriorates as the similarity between the key and the aperture used for decryption decreases, and that the proposed information hiding technique works on actual devices.

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Section: Key Ideasmentioning

confidence: 97%

A Coded Aperture as a Key for Information Hiding Designed by Physics-in-the-Loop Optimization

MINAMATA,

HAMASAKI,

KAWASAKI

et al. 2024

IEICE Trans. Inf. & Syst.

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“…While constrained iterative optimization can provide highquality compensation [17], the computational complexity becomes a bottleneck. This trade-off between computational complexity and image quality can be addressed by using a coded aperture [41] or a DNN-based technique [19], [42]. All the mentioned methods share a common drawback: they require projecting calibration images and estimating the PSF each time the projection setup changes, making them unsuitable for DPM.…”

Section: Projector Deblurringmentioning

confidence: 99%

Efficient Distortion-Free Neural Projector Deblurring in Dynamic Projection Mapping

Kageyama,

Iwai,

Sato

2024

IEEE Trans. Visual. Comput. Graphics

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Dynamic Projection Mapping (DPM) necessitates geometric compensation of the projection image based on the position and orientation of moving objects. Additionally, the projector's shallow depth of field results in pronounced defocus blur even with minimal object movement. Achieving delay-free DPM with high image quality requires real-time implementation of geometric compensation and projector deblurring. To meet this demand, we propose a framework comprising two neural components: one for geometric compensation and another for projector deblurring. The former component warps the image by detecting the optical flow of each pixel in both the projection and captured images. The latter component performs real-time sharpening as needed. Ideally, our network's parameters should be trained on data acquired in an actual environment. However, training the network from scratch while executing DPM, which demands real-time image generation, is impractical. Therefore, the network must undergo pre-training. Unfortunately, there are no publicly available large real datasets for DPM due to the diverse image quality degradation patterns. To address this challenge, we propose a realistic synthetic data generation method that numerically models geometric distortion and defocus blur in real-world DPM. Through exhaustive experiments, we have confirmed that the model trained on the proposed dataset achieves projector deblurring in the presence of geometric distortions with a quality comparable to state-of-the-art methods.

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“…Other applications for flexible focus imaging include 3D shape reconstruction with shape from (de)focus (see e.g. [NN94,ZLN09]) or Confocal Stereo [HK06,HK09], video matting [MMP*05] and extended DOF projection [GWGB10].…”

Section: Extended Depth Of Field Photographymentioning

confidence: 99%

Computational Plenoptic Imaging

Wetzstein¹,

Ihrke²,

Lanman³

et al. 2011

Computer Graphics Forum

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The plenoptic function is a ray-based model for light that includes the colour spectrum as well as spatial, temporal and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two-dimensional, spatially varying subset-the common photograph. In this state-of-the-art report, we review approaches that optically encode the dimensions of the plenoptic function transcending those captured by traditional photography and reconstruct the recorded information computationally.

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Coded aperture projection

Cited by 44 publications

References 30 publications

A Coded Aperture as a Key for Information Hiding Designed by Physics-in-the-Loop Optimization

A Coded Aperture as a Key for Information Hiding Designed by Physics-in-the-Loop Optimization

Efficient Distortion-Free Neural Projector Deblurring in Dynamic Projection Mapping

Computational Plenoptic Imaging

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