We present a computational imaging approach, combining a phase-coded computational camera with a corresponding CNN-based deblurring network, that enables extended depth of field images. The simulations demonstrate promising results achieving significant depth of field extension.Peer reviewe
A key aspect of many computational imaging systems, from compressive cameras to low light photograph...
Computational imaging and sensing leverages the joint-design of optics, detectors and processing to ...
Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrol...
Abstract A computational imaging platform utilizing a physics-incorporated, deep-learned design of b...
We present a learning-based optimization framework for depth of field extension, combining rigorous ...
We present an accommodation-invariant computational neareye display based on the extended depth of f...
Depth of field is an important factor of imaging systems that highly affects the quality of the acqu...
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Deep learning has ...
Most of the neural networks proposed so far for computational imaging (CI) in optics employ a superv...
This electronic version was submitted by the student author. The certified thesis is available in th...
Since the concept of wavefront coding was proposed, many types of phase masks have been reported to ...
Increasing the depth of field (DOF) of compact visible high resolution cameras while maintaining hig...
This paper proposes a digital image restoration algorithm for phase-coded imaging systems. In order ...
Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundament...
An investigation of extended depth-of-field camera with optimized phase mask and digital restoration...
A key aspect of many computational imaging systems, from compressive cameras to low light photograph...
Computational imaging and sensing leverages the joint-design of optics, detectors and processing to ...
Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrol...
Abstract A computational imaging platform utilizing a physics-incorporated, deep-learned design of b...
We present a learning-based optimization framework for depth of field extension, combining rigorous ...
We present an accommodation-invariant computational neareye display based on the extended depth of f...
Depth of field is an important factor of imaging systems that highly affects the quality of the acqu...
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Deep learning has ...
Most of the neural networks proposed so far for computational imaging (CI) in optics employ a superv...
This electronic version was submitted by the student author. The certified thesis is available in th...
Since the concept of wavefront coding was proposed, many types of phase masks have been reported to ...
Increasing the depth of field (DOF) of compact visible high resolution cameras while maintaining hig...
This paper proposes a digital image restoration algorithm for phase-coded imaging systems. In order ...
Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundament...
An investigation of extended depth-of-field camera with optimized phase mask and digital restoration...
A key aspect of many computational imaging systems, from compressive cameras to low light photograph...
Computational imaging and sensing leverages the joint-design of optics, detectors and processing to ...
Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrol...
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