An electronic device providing image data processing and an image data processing method are provided. The electronic device comprises: a display; a reception unit for receiving an input image; and a processor which determines image characteristics of the input image, overlaps a pixel of the input image and a pixel of the display, creates a plurality of resampled images by changing the phase of the pixel of the input image on the basis of the characteristics of the display pixel, performs filtering on each of the plurality of resampled images on the basis of the characteristics of the image, and renders a corrected image on the display by creating the corrected image on the basis of the plurality of resampled images.

An object tracking device includes a storage unit that stores in advance a reference for a movement amount of an object between frames for each position or area on a fisheye image, a determining unit that determines, based on a position of the object in a first frame image and the reference for a movement amount associated with the position of the object in the first frame image, a position of a search area in a second frame image subsequent to the first frame image, and a search unit that searches the search area in the second frame image for the object to specify a position of the object in the second frame image.

Techniques related to calibrating fisheye cameras using a single image are discussed. Such techniques include applying a first pretrained convolutional neural network to an input fisheye image to generate camera model parameters excluding a principle point and applying a second pretrained convolutional neural network to the fisheye image and a difference of the fisheye image and a projection of the fisheye image using the camera model parameters to generate the principle point.

A system and method for determining an absolute position of an object in an area is presented. The system includes a server having a processor, and a plurality of camera nodes coupled to the server. Each node includes a camera that acquires images of the object and area. The server receives image data from a camera, detects the object within an approximate location by image analysis techniques, and determines a relative position of the object in pixel coordinates. The processor then detects stationary markers proximate to the relative location of the object, determines an absolute position of the detected markers relative to known markers to define an absolute position of the marker, and determines an absolute location of the object in relation to the absolute location of the detected marker. This absolute position of the object is provided to an official to accurately locate the object in the area.

Image pair co-registration systems and methods include receiving a pair of multi-modal images, defining a parametric deformation model, defining a loss function that is minimized when the pair of images are aligned, and performing a multi-scale search to determine deformation parameters that minimize the loss function. The optimized deformation parameters define an alignment of the pair of images. The pair of images may include visible spectrum image and an infrared image. The method further includes resizing the visible spectrum image to match the infrared image, applying at least one lens distortion correction model, and normalizing a dynamic range of each of the pair of images. The multi-scale search may further include resizing the pair of images to a current processing scale, applying adaptive histogram equalization to the pair of images to generate equalized images, applying Gaussian Blur to the equalized images, and optimizing the deformation parameters.

A method and an apparatus are for adapting image processing based on a shape of a display device for a motor vehicle. The apparatus includes: a capture device configured to capture a shape of a display device, an extrinsic camera parameter of a camera, an intrinsic camera parameter of the camera, and a of view of the camera; an arithmetic unit configured to calculate a reprojection surface and a correspondence table based on the captured shape of the display device, the extrinsic camera parameter, the intrinsic camera parameter, and the field of view; and an image processing device configured to perform adapted image processing that is adapted based on the reprojection surface and the correspondence table.

Systems and methods for distortion removal at multiple quality levels are disclosed. In one embodiment, a method may include receiving training content. The training content may include original content, reconstructed content, and training distortion quality levels corresponding to the reconstructed content. The reconstructed content may be derived from distorted original content. The method may also include training distortion quality levels corresponding to the reconstructed content. The method may further include receiving an initial distortion removal model. The method may include generating a conditioned distortion removal model by training the initial distortion removal model using the training content. The method may further include storing the conditioned distortion removal model.

Provided is a circuit device used in a display device of a head-up display that performs image projection using display image data and a light source. The circuit device includes: a dimming control circuit configured to perform dimming control of the light source based on image data; a color correction circuit configured to perform color correction on the image data in accordance with a result of the dimming control to output the display image data; and a blinding error detection circuit configured to perform a blinding error detection process of the head-up display in accordance with the display image data and the result of the dimming control.

An apparatus and method for geometrically correcting a distorted input frame and generating an undistorted output frame. The apparatus includes an external memory block that stores the input frame, a counter block to compute output coordinates of the output frame for a region based on a block size of the region, a back mapping block to generate input coordinates corresponding to each of the output coordinates, a bounding module to compute input blocks corresponding to each of the input coordinates, a buffer module to fetch data corresponding to each of the input blocks, an interpolation module to interpolate data from the buffer module and a display module that receives the interpolated data for each of the regions and stitch an output image. The method includes determining the size of the output block based on a magnification data.

An endoscope processor according to one aspect includes an image acquisition unit that acquires a captured image from an endoscope, a first correction unit that corrects the captured image acquired by the image acquisition unit, a second correction unit that corrects the captured image acquired by the image acquisition unit, and an output unit that outputs an endoscopic image based on the captured image corrected by the first correction unit and a recognition result using a trained image recognition model in which the recognition result is output in a case where the captured image corrected by the second correction unit is input.