Systems and methods in accordance with embodiments of the invention are disclosed that use super-resolution (SR) processes to use information from a plurality of low resolution (LR) images captured by an array camera to produce a synthesized higher resolution image. One embodiment includes obtaining input images using the plurality of imagers, using a microprocessor to determine an initial estimate of at least a portion of a high resolution image using a plurality of pixels from the input images, and using a microprocessor to determine a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image. In addition, each forward imaging transformation corresponds to the manner in which each imager in the imaging array generate the input images, and the high resolution image synthesized by the microprocessor has a resolution that is greater than any of the input images.

Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

A system and method for obtaining a target image are provided. The system includes: a floodlight illumination source configured to provide illumination of a first wavelength for a target area; a first acquisition camera configured to acquire a target floodlight image of the first wavelength of the target area; a structured light projector configured to project a structured light image of a second wavelength to the target area; a second acquisition camera configured to acquire the structured light image of the target area; and a processor, connected to the floodlight illumination source, the first acquisition camera, the structured light projector, and the second acquisition camera, and configured to: acquire the target floodlight image and the structured light image; recognize a foreground target in the floodlight image; and extract a target structured light image based on a relative position relationship between the first acquisition camera and the second acquisition camera.

An image sensor, a mobile terminal and a photographing method are provided. The image sensor includes: a pixel array, where the pixel array includes a preset quantity of pixel units arranged in a predetermined manner, the pixel unit includes a first pixel and a second pixel adjacent to the first pixel, the first pixel includes a red subpixel, a green subpixel, and a blue subpixel, the second pixel includes a red subpixel, a green subpixel, and an infrared subpixel, and both the first pixel and the second pixel are dual photodiode pixels, where a location of the blue subpixel in the first pixel is the same as that of the infrared subpixel in the second pixel, and each of the first pixel and the second pixel includes four dual photodiode subpixels.

Disclosed are an image processing method and apparatus, and an image processing device. According to the image processing method and apparatus, and the image processing device, an infrared binocular camera collects images formed when a measured object is illuminated by a speckle pattern projected by a projection assembly to obtain a first image collected by a first camera and a second image collected by a second camera; and three-dimensional data of the measured object is determined according to a pair of images constituted by the first image and the second image. By means of the method, three-dimensional data of a measured object can be relatively accurately obtained through measurement, thereby improving precision and accuracy of measurement, and also precision requirements for a projection assembly are low, so that costs can be lowered.

An image signal processor includes a register and a disparity correction unit. The register stores disparity data obtained from a pattern image data that an image senor generates, and the image sensor includes a plurality of pixels, and each of the pixel includes at least a first photoelectric conversion element and a second photoelectric conversion element. The image sensor generates the pattern image data in response to a pattern image located at a first distance from the image sensor. The disparity correction unit corrects a disparity distortion of an image data based on the disparity data to generate a result image data, and the image senor generates the image data by capturing an object.

An image signal processor includes a register and a disparity correction unit. The register stores disparity data obtained from a pattern image data that an image senor generates, and the image sensor includes a plurality of pixels, and each of the pixel includes at least a first photoelectric conversion element and a second photoelectric conversion element. The image sensor generates the pattern image data in response to a pattern image located at a first distance from the image sensor. The disparity correction unit corrects a disparity distortion of an image data based on the disparity data to generate a result image data, and the image senor generates the image data by capturing an object.

An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.

An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.