Super Field-of-View Lensless Camera by Coded Image Sensors

Area of Science:

• Computational Imaging
• Optics
• Materials Science

Background:

• Existing lensless cameras have limitations in capturing both sides of an object due to their axial sensor and coding mask arrangement.
• The back side of the image sensor is inaccessible in conventional lensless camera designs.

Purpose of the Study:

• To propose and validate a novel lensless camera design capable of simultaneous front and back side imaging.
• To overcome the limitations of existing lensless camera systems for enhanced information capture.

Main Methods:

• The proposed camera employs multiple coded complementary-metal-oxide-semiconductor (CMOS) image sensors with randomly drilled air holes.
• One CMOS sensor acts as a coding mask, while another functions as a sparsified image sensor when placed facing each other.
• Image reconstruction is performed computationally using compressive sensing algorithms.

Main Results:

• Feasibility of the novel lensless camera design was confirmed through both simulations and experimental validation.
• The system achieved super-field-of-view imaging without the need for traditional lenses or external coding masks.
• Demonstrated the capability for rich information sensing in space-constrained environments.

Conclusions:

• The developed thin lensless camera offers a new paradigm for imaging in confined spaces.
• This innovative design opens new avenues for complementary-metal-oxide-semiconductor (CMOS) image sensor development in the field of computational imaging.
• The system enables simultaneous dual-sided imaging, expanding the utility of lensless camera technology.