A bijective coded aperture system uses mirror system with a multitude of reflector elements attached to an absorbing, such as black, substrate. Each of the reflector elements is independently placed at a different angle with respect to each other in such a manner that the image of the scene is replicated several times at the focal plane and on the image sensor. Moreover, these replicated images may be overlapping. An image processor can then execute reconstruction methods of the image to faithfully represent the scene.

Computational refocusing-assisted deep learning methods, apparatus, and systems are described. In certain pathology examples, a representative image is generated using a machine learning model trained with uniformly focused training images generated by a Fourier ptychographic digital refocusing procedure and abnormalities are automatedly identified and/or enumerated based on the representative image.

A field of view of a captured image of a lensless camera can be controlled, and a configuration of generating a restored image including part of an imaging region is realized. Included is a signal processing unit that receives observed image signals as output of an image sensor of a lensless camera to generate a restored image of a restored image region including part of a captured image region of the lensless camera. The signal processing unit includes: a restored image region corresponding mask matrix calculation unit that calculates a restored image region corresponding mask matrix applied to generate the restored image; and an image estimation unit that subtracts observed image signals outside of the restored image region not included in the restored image region from the observation image signals to calculate observed image signals inside of the restored region and that executes arithmetic processing of the observed image signals inside of the restored region and a pseudo-inverse matrix or an inverse matrix of the restored image region corresponding mask matrix to generate the restored image.

The present technology relates to an information processing device, an information processing method, a program, and an information processing system for enabling reduction in a load by enabling selective arithmetic processing in performing imaging without using an imaging lens. The information processing device includes an acquisition unit configured to acquire a detection image output from an imaging element that receives incident light incident without through an imaging lens, and restoration information including setting information set by a user and to be used to generate a restoration image from the detection image, a restoration processing unit configured to perform restoration processing of generating the restoration image using the detection image and the restoration information, and an output control unit configured to control an output of the restoration image. The present technology can be applied to, for example, a device or a system that restores a detection image captured by a lensless camera.

In one embodiment, a camera includes an image sensor within a camera housing that converts light entering the camera housing through an optical filter into digital image data. The optical filter can have a variable opacity. A processor in communication with the image sensor identifies operation settings for the optical filter and adjusts an opacity level of the optical filter over an exposure period in accordance with the operation settings for the optical filter. In addition, the processor modifies values of the digital image data based at least on the operation settings for the optical filter.

An imaging system uses a dynamically varying coded mask, such as a spatial light modulator (SLM), to time-encode multiple degrees of freedom of a light field in parallel and a detector and processor to decode the encoded information. The encoded information may be decoded at the pixel level (e.g., with independently modulated counters in each pixel), on a read-out integrated circuit coupled to the detector, or on a circuit external to the detector. For example, the SLM, detector, and processor may create modulation sequences representing a system of linear equations where the variables represent a degree of freedom of the light field that is being sensed. If the number of equations and variables form a fully determined or overdetermined system of linear equations, the system of linear equations' solution can be determined through a matrix inverse. Otherwise, a solution can be determined with compressed sensing reconstruction techniques with the constraint that the signal is sparse in the frequency domain.

A compressed sensing imaging method and a compressed sensing imaging system are provided. In the method, multiple grayscale masks having multiple elements with grayscale values represented by floating-point values or continuous values are generated as sensing matrices based on a compressed sensing theory. A spatial light modulator is controlled to modulate an electromagnetic wave projected on an object under test according to the grayscale value of each element in each grayscale mask, and a physical property of the electromagnetic wave passing through the object under test is detected to obtain multiple measured values. An image reconstruction algorithm is executed to reconstruct an image of the object under test by using the grayscale masks and the measured values obtained from the electromagnetic wave modulated by each grayscale mask.

A near-eye display device includes at least one projection system configured to project an image to a target position. The projection system includes an image output module, an object lens group, an aperture-coded module, and an eyepiece. The image output module is configured to provide the image. The object lens group is configured to receive lights of the image, and includes a first lens group and a second lens group. The aperture-coded module is configured to receive the lights of the image from the first lens group and send the lights of the image to the second lens group, and the aperture-coded module sequentially provides plural coded patterns, such that the object lens group converts the image into plural relay images sequentially. The eyepiece is configured to send the relay images to the target position.

A spectral imaging system comprises: a spatial encoder comprising a first light encoding device comprising a first mask for spatial encoding, the first mask being configured with one or more encoding patterns; a spectral encoder comprising: a dispersion arrangement for splitting spatially encoded light from the first light encoding device into a plurality of components; and a second light encoding device comprising a second mask for spectral encoding of the plurality of components, the second mask having one or more encoding patterns; and at least one single-pixel photodetector positioned to measure light that is encoded by the masks. The spatial encoder is operable to spatially encode light by generating a sequence of different patterns or partial patterns of the one or more encoding patterns of the first mask. The spectral encoder is operable to spectrally encode light by relative movement between the dispersion arrangement and the second mask.

A device and method for three-dimensional (3-D) imaging using a defocusing technique is disclosed. The device comprises a lens, a central aperture located along an optical axis for projecting an entire image of a target object, at least one defocusing aperture located off of the optical axis, a sensor operable for capturing electromagnetic radiation transmitted from an object through the lens and the central aperture and the at least one defocusing aperture, and a processor communicatively connected with the sensor for processing the sensor information and producing a 3-D image of the object. Different optical filters can be used for the central aperture and the defocusing apertures respectively, whereby a background image produced by the central aperture can be easily distinguished from defocused images produced by the defocusing apertures.