In one general aspect, a method can include capturing, using an image sensor, a first raw image at a first resolution, converting the first raw image to a digitally processed image using an image signal processor, and analyzing at least a portion of the digitally processed image based on a processing condition. The method can include determining that the first resolution does not satisfy the processing condition; and triggering capture of a second raw image at the image sensor at a second resolution greater than the first resolution.

An imaging system including an imaging device 501 and a recording server 502 communicatively connected to the imaging device 501, wherein the imaging device 501 includes an imaging unit 503 that generates a video with a plurality of resolution, a dividing unit 504 that performs a division process of dividing the video generated by the imaging unit 503 into one or a plurality of tile areas and generates a tile image, and a transmission unit 506 that transmits the video to the recording server 502, wherein the recording server 502 includes a division control unit 507 that outputs an instruction to change a division method for the division process to the imaging device according to a designation frequency of an area designated on the video transmitted from the imaging device 501.

An image-capturing device includes: a photographic optical system; a photoelectric conversion element array made up with a plurality of photoelectric conversion elements arrayed therein; a micro-lens array made up with a plurality of micro-lenses arrayed therein; a data creation unit that creates pixel data at a plurality of pixels on a specific image forming plane by applying filter matrix data to output signals provided from the plurality of photoelectric conversion elements; and an image synthesis unit that synthetically generates an image on the specific image forming plane at a given position assumed along an optical axis of the photographic optical system, based upon the pixel data. The filter matrix data assume a two-dimensional data array pattern conforming to a specific intensity distribution with a distribution center thereof set at an element corresponding to a central position of a projection image of each of the plurality of pixels.

A view system for a vehicle (1) with a tractor (2) and a trailer (3). The view system has a capture unit (10) with an image sensor (12) for capturing image data of an area of view, around the vehicle, a processing unit (20) for processing the image data, and a reproduction unit (30) for reproducing at least one first image section (410) and one second image section (420) of the area of view (40) captured by the capture unit (10). The processing unit provides different resolutions of image data depending on the position of the tractor with respect to the trailer.

An imaging device, according to one embodiment of the present invention, comprises: an input unit for receiving first Bayer data having a first resolution and a noise level; and a convolutional neural network for outputting second Bayer data having a second resolution by using the noise level and the first Bayer data.

To satisfactorily detect an edge detection signal of a high frequency band from a captured image signal at all times. A filtering unit extracts an edge detection signal of a high frequency band from an image signal obtained from imaging, and a band control unit controls the high frequency band on the basis of lens information. For example, the filtering unit includes a first high-pass filter with a first cutoff frequency, a second high-pass filter with a second cutoff frequency that is lower than the first cutoff frequency, and an α blending unit that performs α blending on output of the first high-pass filter and output of the second high-pass filter. Even if the frequency of the edge detection signal included in the captured image signal varies due to a change in a zoom position, a lens model number, an F value or the like, the edge detection signal can be satisfactorily detected at all times.

An image processing method and a device, where the image processing method is performed by a terminal having a digital zoom function, and the method includes determining a target zoom magnification based on a selection input of a user, collecting a to-be-processed image, and processing the to-be-processed image using a target super-resolution convolutional neural network model to obtain a processed image corresponding to the target zoom magnification, where the target super-resolution convolutional neural network model is obtained by training a super-resolution convolutional neural network model using a high-definition training image, a low-definition training image, and a mask image.

An imaging system including an imaging device 501 and a recording server 502 communicatively connected to the imaging device 501, wherein the imaging device 501 includes an imaging unit 503 that generates a video with a plurality of resolution, a dividing unit 504 that performs a division process of dividing the video generated by the imaging unit 503 into one or a plurality of tile areas and generates a tile image, and a transmission unit 506 that transmits the video to the recording server 502, wherein the recording server 502 includes a division control unit 507 that outputs an instruction to change a division method for the division process to the imaging device according to a designation frequency of an area designated on the video transmitted from the imaging device 501.

Reduction of recorded noise is achieved at the time of imaging in an environment of generation of noticeable noise while securing user convenience. A communication controller includes a wireless communication unit that performs first wireless communication using a first wireless communication method, and second wireless communication using a second wireless communication method, and a control unit that detects a volume of a voice, and changes a wireless output of the first wireless communication on the basis of the detected volume.

An image sensing device includes an analysis module suitable for analyzing, based on pixel values of a kernel, an image texture of the kernel including a target pixel group and one or more adjacent pixel groups, a sum module suitable for generating any one of a first target sum value and a second target sum value based on an analysis result of the analysis module, wherein first target sum value is obtained by applying texture characteristics of the kernel in target pixel values of the target pixel group and the second target sum value is obtained without applying the texture characteristics of the kernel in the target pixel values, and a processing module suitable for generating a sum image based on any one of the first and second target sum values.