An image capturing apparatus including a lens and a processing unit, wherein the lens includes a first region through which a first light ray passes and a second region through which a second light ray passes, wherein the first region and the second region are arranged in a predetermined direction, and wherein the processing unit sets a component of the predetermined direction as a degree of freedom in a first relative positional relationship between a predetermined position in the first region and a predetermined position in the second region is employed.

Indirect time-of-flight (i-ToF) image sensor pixels, i-ToF image sensors including such pixels, stereo cameras including such image sensors, and sensing methods to obtain i-ToF detection and phase detection information using such image sensors and stereo cameras. An i-ToF image sensor pixel may comprise a plurality of sub-pixels, each sub-pixel including a photodiode, a single microlens covering the plurality of sub-pixels and a read-out circuit for extracting i-ToF phase signals of each sub-pixel individually.

The present disclosure provides a light field imaging system by projecting near-infrared spot in remote sensing based on a multifocal microlens array. The light field imaging system includes a near-infrared spot projection apparatus (100) and a light field imaging component (200), where the near-infrared spot projection apparatus (100) is configured to scatter near-infrared spots on a to-be-observed object to add texture information to a target image, and the light field imaging component (200) is configured to image a target scene light ray with additional texture information. The present disclosure can extend a target depth-of-field (DOF) detection range, and particularly, reconstruct a surface of a weak-texture object.

The present disclosure provides a light field imaging system by projecting near-infrared spot in remote sensing based on a multifocal microlens array. The light field imaging system includes a near-infrared spot projection apparatus (100) and a light field imaging component (200), where the near-infrared spot projection apparatus (100) is configured to scatter near-infrared spots on a to-be-observed object to add texture information to a target image, and the light field imaging component (200) is configured to image a target scene light ray with additional texture information. The present disclosure can extend a target depth-of-field (DOF) detection range, and particularly, reconstruct a surface of a weak-texture object.

System, methods, and other embodiments described herein relate to estimating depth using a machine learning (ML) model. In one embodiment, a method includes acquiring image data according to criteria from a detector that uses a lens to resolve multiple angles of light per section of the detector. The method also includes mapping a kernel to the image data according to a view associated with the section and a size of the kernel. The method also includes processing the image data using the ML model to produce the depth according to the size of the kernel.

There is provided a depth information generating apparatus. A first generating unit generates first depth information on the basis of a plurality of viewpoint images which are obtained from first shooting and which have mutually-different viewpoints. A second generating unit generates second depth information for a captured image obtained from second shooting by correcting the first depth information so as to reflect a change in depth caused by a difference in a focal distance of the second shooting relative to the first shooting.

Depths of one or more objects in a scene may be measured with enhanced accuracy through the use of a light-field camera and a depth sensor. The light-field camera may capture a light-field image of the scene. The depth sensor may capture depth sensor data of the scene. Light-field depth data may be extracted from the light-field image and used, in combination with the sensor depth data, to generate a depth map indicative of distance between the light-field camera and one or more objects in the scene. The depth sensor may be an active depth sensor that transmits electromagnetic energy toward the scene; the electromagnetic energy may be reflected off of the scene and detected by the active depth sensor. The active depth sensor may have a 360° field of view; accordingly, one or more mirrors may be used to direct the electromagnetic energy between the active depth sensor and the scene.

Provided is an electronic device, wherein the at least one processor is configured to execute the at least one instruction to obtain a first light field image including view images with a first number of views, obtain, from the first light field image, a second light field image including view images with a second number of views, obtain first location information corresponding to each of sub-pixels in the second light field image, obtain a first layer image by inputting the second light field image and the first location information to an artificial intelligence model configured to perform factorization, obtain a third light field image including view images with a third number of views by inputting the first layer image to a simulation model, and train the artificial intelligence model, based on a result of comparing the first light field image and the third light field image with each other.

An image processing method and apparatus are provided. The image processing apparatus includes an interface configured to output an input frame and metadata including type information and subtype information; and a rendering unit configured to: determine a type of a polyhedron included in an output frame based on the type information, determine attributes of arrangement of a plurality of areas included in the input frame based on the subtype information, and render the output frame by mapping each of the plurality of areas to corresponding faces of the polyhedron, based on the attributes of arrangement of the plurality of areas.

An image processing apparatus comprises: an acquisition unit configured to acquire a first viewpoint image corresponding to a first partial pupil region of an exit pupil of as imaging optical system divided into a plurality of partial pupil regions in a first direction, and a captured image corresponding to the exit pupil; and a correction unit configured to correct shading of a first pixel of a first pixel group based on a first ratio of a sum of the first pixel group of the first viewpoint image arranged in a second direction orthogonal to the first direction to a sum of a pixel group of the captured image corresponding to a position of the first pixel group.