A multispectral image sensor includes a plurality of photosensitive elements configured to capture electromagnetic radiation received from a scene or an object, and first and second optical modulators arranged on an incident side of the plurality of photosensitive elements. The first and second optical modulators are configured to modulate electromagnetic radiation within respective first and second wavelength ranges, and to transmit electromagnetic radiation outside the respective first and second wavelength ranges. The first wavelength range is different from the second wavelength range.

A computer device obtains a confocal microscopy image. The device determines a pinhole diameter of a first detector pinhole of a confocal microscope that is used to acquire the image. The pinhole diameter has an influence on a parameter of the image. The device obtains a target image processing model corresponding to the pinhole diameter of the first detector pinhole. The target image processing model is configured to improve the parameter of the image. The device causes the target image processing model to process the image to obtain a target image having the improved parameter.

A computer device obtains a confocal microscopy image. The device determines a pinhole diameter of a first detector pinhole of a confocal microscope that is used to acquire the image. The pinhole diameter has an influence on a parameter of the image. The device obtains a target image processing model corresponding to the pinhole diameter of the first detector pinhole. The target image processing model is configured to improve the parameter of the image. The device causes the target image processing model to process the image to obtain a target image having the improved parameter.

Provided is an imaging system including a phase mask including a phase modulation meta surface coded with an image reconstruction phase function configured to reconstruct an image, the image reconstruction phase function being obtained by adding a first phase function corresponding to a lens phase to a second phase function which is a random function, and an image sensor configured to convert light, transmitted through the phase mask from an object, into an electrical signal.

Provided is an imaging system including a phase mask including a phase modulation meta surface coded with an image reconstruction phase function configured to reconstruct an image, the image reconstruction phase function being obtained by adding a first phase function corresponding to a lens phase to a second phase function which is a random function, and an image sensor configured to convert light, transmitted through the phase mask from an object, into an electrical signal.

Systems and methods are described for enabling a lensless camera having an image sensor and a mask to be positioned behind a display screen of a device, which allows for the device to have an increased screen-to-body ratio. The image sensor captures an image based on the light that travels through the display screen and the mask. The display screen may include portions between pixel elements that allow light to pass through. The mask may include a pattern, such as an opaque material with portions that allow light to pass through from the portions of the display layer to the image sensor. The image captured by the image sensor may be indiscernible to humans. The system may utilize a trained machine learning model to reconstruct the image, using data about the pattern of the mask, so humans may visually recognize features in the image.

Systems and methods are described for enabling a lensless camera having an image sensor and a mask to be positioned behind a display screen of a device, which allows for the device to have an increased screen-to-body ratio. The image sensor captures an image based on the light that travels through the display screen and the mask. The display screen may include portions between pixel elements that allow light to pass through. The mask may include a pattern, such as an opaque material with portions that allow light to pass through from the portions of the display layer to the image sensor. The image captured by the image sensor may be indiscernible to humans. The system may utilize a trained machine learning model to reconstruct the image, using data about the pattern of the mask, so humans may visually recognize features in the image.

A machine vision system and method use lensless near-contact imaging with coherent illumination, or incoherent illumination, and high pixel count large format sensors (e.g., equivalent to at least 20 to 65 mega-pixels) to produce diffraction patterns of the micro-objects or the gray scale images of the micro-objects over a large overall field-of-view of the machine vision system. The machine vision system provides feedback to a microassembler system to position, orient, and assemble microscale devices like micro-LEDs over large working areas. The effective resolution of the machine vision system can be further improved through the use of gray scale and super-resolution image processing techniques.

A machine vision system and method use lensless near-contact imaging with coherent illumination, or incoherent illumination, and high pixel count large format sensors (e.g., equivalent to at least 20 to 65 mega-pixels) to produce diffraction patterns of the micro-objects or the gray scale images of the micro-objects over a large overall field-of-view of the machine vision system. The machine vision system provides feedback to a microassembler system to position, orient, and assemble microscale devices like micro-LEDs over large working areas. The effective resolution of the machine vision system can be further improved through the use of gray scale and super-resolution image processing techniques.

The present disclosure relates to an image processing apparatus, an image processing method, and a program capable of realizing highly accurate image recognition processing while taking privacy into consideration with a simple configuration. A mask of a lensless camera is convoluted with a weight of a DNN first layer used in image recognition processing using a DNN, and a reconstructed image becomes a processing result of the DNN first layer on the basis of a captured image captured by an image sensor. Accordingly, the restored image becomes the processing result of the DNN first layer and becomes an image difficult for a person to visually recognize as a scene or an object, making it possible to protect the privacy of the image. The present disclosure can be applied to an image recognition apparatus using a lensless camera.