Abstract
Computational imaging describes the whole imaging process from the perspective of light transport and information transmission, features traditional optical computing capabilities, and assists in breaking through the limitations of visual information recording. Progress in computational imaging promotes the development of diverse basic and applied disciplines. In this review, we provide an overview of the fundamental principles and methods in computational imaging, the history of this field, and the important roles that it plays in the development of science. We review the most recent and promising advances in computational imaging, from the perspective of different dimensions of visual signals, including spatial dimension, temporal dimension, angular dimension, spectral dimension, and phase. We also discuss some topics worth studying for future developments in computational imaging.
Highlights
As one of the most important information carriers in the physical world, high-dimensional continuous light signals can be recorded at a significantly high quality in each dimension, due to the rapid development of imaging techniques
Computational imaging has achieved a great success in the past years, and some work has even been applied in various fields
We will discuss some trends in computational imaging
Summary
As one of the most important information carriers in the physical world, high-dimensional continuous light signals can be recorded at a significantly high quality in each dimension (space, time, angle, spectrum, and phase), due to the rapid development of imaging techniques. Different from conventional imaging methods, computational imaging first couples the target information using new optical devices or materials, and designs new imaging mechanisms to modulate light in a specific way. Using the strong computation ability of modern computation resources, researchers design the corresponding reconstruction methods to restore the target visual information. Sometimes, further modulations, such as feedback loops, are introduced into the imaging systems to achieve the imaging goal. Unlike conventional imaging methods which rely on readily available imaging devices, computational imaging techniques treat the whole imaging process systematically and target the capturing of high-dimensional, multi-scale, diverse, and highquality visual information. Computational imaging overcomes the limitations of conventional imaging methods and brings distinctively new insights and opportunities into the development of related fields, such as life and biomedical sciences, materials science, computer vision, and graphics
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