A depth acquisition device includes a memory and a processor. The processor performs; acquiring timing information indicating a timing at which a light source irradiates a subject with infrared light; acquiring an infrared light image stored in the memory, the infrared light image being generated by imaging a scene including the subject with the infrared light according to the timing indicated by the timing information; acquiring a visible light image stored in the memory, the visible light image being generated by imaging a substantially same scene as that of the infrared light image, with visible light from a substantially same viewpoint and at a substantially same imaging time of those of the infrared light image; detecting a dust region showing dust from the infrared light image; and estimating a depth of the dust region based on the infrared light image, the visible light image, and the dust region.

Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

A detector detects an overall fill level of a receiving vehicle. A mobile device on the receiving vehicle includes a mobile application that receives and displays the overall fill level of the receiving vehicle. The overall fill level can be overlaid on a geographic map that shows locations of multiple receiving vehicles, in which case an overall fill level indicator for each receiving vehicle is displayed on the geographic map as well.

Device (100) for attesting the operations of an in-vitro diagnostic device (50) comprising: a block (101) for capturing a plurality of frames of the tip (51); a block (102) for storing the plurality of frames; a block (103) for evaluating the right hooking of the tip (51) to the in-vitro diagnostic device (50); a block (104) for evaluating the volume of a liquid contained in the tip (51); a block (105) for carrying out verification before the operation of dispensing the liquid; a block (106) for carrying out a post-dispensing verification; blocks (107, 108) for emitting electronic signals; a block (109) for integrating a system for managing the errors; a block (110) for saving the data; a block (111) for communicating with the in-vitro diagnostic device (50).

An electronic device includes at least one imaging sensor and at least one processor coupled to the at least one imaging sensor. The at least one imaging sensor is configured to capture a burst of image frames. The at least one processor is configured to generate a low-resolution image from the burst of image frames. The at least one processor is also configured to estimate a blur kernel based on the burst of image frames. The at least one processor is further configured to perform deconvolution on the low-resolution image using the blur kernel to generate a deconvolved image. In addition, the at least one processor is configured to generate a high-resolution image using super resolution (SR) on the deconvolved image.

Methods and systems provide for video appearance adjustments within a video communication session. First, the system receives video content. The system then receives an appearance adjustment request comprising an adjustment depth, and detects imagery of a user within the video content. The system then detects a face region within the video content. The system segments the face region into a number of skin areas. For each of the plurality of skin areas, the system classifies the skin area as a smooth texture region or rough texture region. If the skin area is classified as a smooth texture region, the system modifies the imagery of the user in real time or substantially real time by applying a smoothing process to the skin area, where the amount of smoothing applied corresponds to the adjustment depth.

Systems and methods are provided for performing temporally consistent depth map generation by implementing acts of obtaining a first stereo pair of images of a scene associated with a first timepoint and a first pose, generating a first depth map of the scene based on the first stereo pair of images, obtaining a second stereo pair of images of the scene associated with at a second timepoint and a second pose, generating a reprojected first depth map by reprojecting the first depth map to align the first depth map with the second stereo pair of images, and generating a second depth map that corresponds to the second stereo pair of images using the reprojected first depth map.

This disclosure relates generally to a system and method for monitoring performance of low-cost sensors plied in a field for soil moisture measurement. The low-cost sensors are calibrated to give useful derived parameters to support farming such as volumetric water content (VWC) of the soil. Further, the steps are being incorporated to de-noise their response to derive stable measurements similar to expensive rugged sensors. The calibration of the low-cost sensor and normalization of incoming values from the low-cost sensor are based on values determined through rugged sensors for soil moisture measurement. The normalization involves finding a minimum value and maximum value of soil moisture. Performance of the low-cost sensors are analyzed based on a range of values of the soil moisture. Finally, the performance analysis provides degradation stages and based on the degradation stages evaluated recommendations to modify the sensor are shared with the user.

Provided is an image processing apparatus including a memory storing at least one instruction; and a processor configured to execute the at least one instruction to: obtain, from a first image, a second image from which noise has been removed using a filtering algorithm; determine first weight data corresponding to the first image and second weight data corresponding to the second image, by applying the first image to a neural network for deriving a mixing ratio between the first image and the second image; and obtain an output image by mixing a first result obtained by applying the first weight data to the first image, with a second result obtained by applying the second weight data to the second image.

The present disclosure relates to systems and methods for image processing. The method may include receiving an original image including a plurality of pixels; determining a plurality of smoothed images by applying a plurality of filtering kernels to the plurality of pixels of the original image, wherein each of the plurality of filtering kernels may be associated with a respective kernel size; determining a plurality of enhanced images by comparing the original image with the plurality of smoothed images; and generating a target image based on at least one of the plurality of enhanced images and at least one of: the original image or at least one of the plurality of smoothed images.