A system and method for creating small data size representations of images, created on the image detection device, over wireless connections when there is insufficient bandwidth to support detailed images is disclosed. Image data size is often too large to send over low-powered long-distance wireless connections. Image data must be dramatically reduced to enable use of the lowest-power longest-distance wireless platforms including LoRa with LoRaWAN. Common image compression algorithms include jpeg and mpeg that provide only moderate reductions in data size. The described invention reduces data size beyond jpeg compression by reducing targeted image objects to simple outlines, contours or vectors. Monitoring security, wildlife, agricultural and other natural events require images of objects including insects, crops, livestock, wildlife or intruders. Contours, outlines or vectors of targeted objects are often sufficiently recognizable to provide useful information.

A system and method for creating small data size representations of images, created on the image detection device, over wireless connections when there is insufficient bandwidth to support detailed images is disclosed. Image data size is often too large to send over low-powered long-distance wireless connections. Image data must be dramatically reduced to enable use of the lowest-power longest-distance wireless platforms including LoRa with LoRaWAN. Common image compression algorithms include jpeg and mpeg that provide only moderate reductions in data size. The described invention reduces data size beyond jpeg compression by reducing targeted image objects to simple outlines, contours or vectors. Monitoring security, wildlife, agricultural and other natural events require images of objects including insects, crops, livestock, wildlife or intruders. Contours, outlines or vectors of targeted objects are often sufficiently recognizable to provide useful information.

Adaptive control systems using augmented and virtual reality systems chimerically integrated with Artificial Intelligence and the like Homunculi fix vision issues with data based and user tuned solutions in real time.

An image capturing system includes a light source configured to emit light toward an object or scene that is to be imaged. The system also includes a time-of-flight image sensor configured to receive light signals based on reflected light from the object or scene. The system also includes a processor operatively coupled to the light source and the time-of-flight image sensor. The processor is configured to perform compressive sensing of the received light signals. The processor is also configured to generate an image of the object or scene based at least in part on the compressive sensing of the received light signals.

Disclosed are a depth image processing method, a depth image processing apparatus (10), and an electronic device (100). The depth image processing method is applied in the electronic device (100) including a depth image capturing apparatus (20) configured to capture an initial depth image. The depth image processing method includes: obtaining (01) target depth data for a number of regions of interest of the initial depth image; determining (02) whether the number of regions of interest is greater than a predetermined value; grouping (03), in response to the number of regions of interest being greater than the predetermined value, the number of regions of interest based on the target depth data to obtain a target depth of field; obtaining (04) a target blurring intensity based on the target depth of field; and blurring (05) the initial depth image based on the target blurring intensity to obtain a blurred depth image.

Provided is an image sensor including a pixel array formed by arranging pixels, which generate an electrical signal in response to light; a memory for storing a register value of the image sensor; and a sensor controller for configuring the register value, wherein the register value includes information for defining a region to be processed in the pixel array, and when a change request for changing at least one of a position and a size of the region to be processed is received, the sensor controller provides a register modification command for adjusting the register value so as to correspond to the change request to the image sensor or the memory.

An electronic device and method are provided. The electronic device includes a camera, a communication circuit, and a processor configured to be operably coupled to the camera and the communication circuit. The processor is further configured to receive first image data from the camera by controlling the camera based on a first parameter, transmit the first image data to an external electronic device by using the communication circuit in response to acquisition of the first image data, identify a second parameter for controlling the camera at least based on the external electronic device having received the first image data, and acquire second image data by controlling the camera based on the second parameter in response to the identification of the second parameter.

A meta lens assembly includes a first meta lens, a second meta lens arranged on an image side of the first meta lens, and a third meta lens arranged on an image side of the second meta lens, the first meta lens, the second meta lens, and the third meta lens being arranged from an object side of the meta lens assembly to an image side of the meta lens assembly facing an image sensor.

The present disclosure provides an image encoder. The image encoder is configured to encode an original image and reduce compression loss. The image encoder comprises an image signal processor and a compressor. The image signal processor is configured to receive a first frame image and a second frame image and generates a compressed image of the second frame image using a boundary pixel image of the first frame image. The image signal processor may include memory configured to store first reference pixel data which is the first frame image. The compressor is configured to receive the first reference pixel data from the memory and generate a bitstream obtained by encoding the second frame image based on a difference value between the first reference pixel data and the second frame image. The image signal processor generates a compressed image of the second frame image using the bitstream generated by the compressor.

Methods and systems are provided for providing directional assistance to guide a user to position a camera for centering a person's face within the camera's field of view. A neural network system is trained to determine the position of the user's face relative to the center of the field of view as captured by an input image. The neural network system is trained using training input images that are generated by cropping different regions of initial training images. Each initial image is used to create a plurality of different training input images, and directional assistance labels used to train the network may be assigned to each training input image based on how the image is cropped. Once trained, the neural network system determines a position of the user's face, and automatically provides a non-visual prompt indicating how to center the face within the field of view.