Abstract: An image evaluation method, including: obtaining a test image including a first lattice pattern formed by image edges; aligning the test image using the image edges to generate an aligned image including a second lattice pattern formed by aligned image edges; generating a compressed image by compressing the aligned image; and generating a quantified result by quantifying a per-pixel difference between the compressed image and the aligned image.

Abstract: A system for testing whether or not an image sensor included in an image frame is defective includes including a processor configured to execute machine-readable instructions that, when executed by the processor, cause the test device to generate a test image by performing one or more preprocessing operations on a raw image output from an image sensor, and to classify an image pattern of the test image as any one of patterns included in a first data set by using a first deep learning neural network trained based on the first data set and to determine, based on a classifying result, whether or not the image sensor is defective. The first data set comprises a data set for each pattern, classified to correspond to each of one or more defect patterns and to a normal pattern of an image.

Abstract: An image sensor including a pixel array in which a plurality of pixels are arranged, and a nano-condensing lens array including a plurality of condensing areas respectively corresponding to the plurality of pixels. Each of the plurality of condensing areas includes at least one nanostructure that condenses light on a corresponding pixel among the plurality of pixels, and the at least one nanostructure is arranged in each of the plurality of condensing areas such that a condensing capability of the at least one nanostructure included in each of the plurality of condensing areas varies according to a distance from a center of the nano-condensing lens array to each of the plurality of condensing areas.

Abstract: Disclosed is a camera module which includes an image sensor including pixels outputting raw image data based on light incident from at least one of a display or the exterior, and control logic receiving the raw image data and generating image data. In a first operation mode, the control logic turns off calibration of the image sensor, receives first raw image data, which are based on the light incident from the display, from the image sensor, and generates crosstalk calibration data based on first output values included in the first raw image data. In a second operation mode, the control logic turns on the calibration of the image sensor, receives second raw image data, which are based on light incident from the display and the exterior, from the image sensor, and generates the image data based on second output values included in the second raw image data.

Abstract: An image processing device includes an image sensor including a pixel array that includes a first pixel group, and a correlated double sampling circuit. The first pixel group includes a first plurality of normal pixels, a second plurality of normal pixels, and at least one first phase detection pixel. The correlated double sampling circuit is configured to generate first video data, based on charges of the first plurality of normal pixels, generate second video data, based on charges of the second plurality of normal pixels, and generate first phase detection data, based on an output of the at least one first phase detection pixel. The image processing device further includes an image signal processor configured to apply a first weight to the generated first video data, and apply a second weight to the generated second video data.

Abstract: Disclosed is a device for noise reduction using dual conversion gain, which includes an image sensor including a pixel array, the pixel array configured to generate a first pixel signal corresponding to a first conversion gain and a second pixel signal corresponding to a second conversion gain from pixels sharing a floating diffusion region and the image sensor configured to generate first image data and second image data based on the first pixel signal and the second pixel signal, and an image signal processor that generates an output image based on the first image data and the second image data. The image signal processor includes a normalization circuit that normalizes the first image data based on a dynamic range of the second image data to generate third image data, and a blending circuit that generates the output image based on the second image data and the third image data.

Abstract: An electronic device includes a frequency analyzing circuit and a color difference calculating circuit. The frequency analyzing circuit receives an image signal including information about a subject, may convert the image signal into first color data which are based on a first color domain, converts the first color data into frequency data which are based on a frequency domain, and applies frequency weights corresponding to the frequency data to the first color data to generate processed color data. The color difference calculating circuit calculates color difference values for evaluating a color stain generated by the image signal, based on the processed color data. The frequency weights are selected based on sensitivity information of an observer according to a frequency change of the frequency data.

Abstract: An image evaluation method, including: obtaining a test image including a first lattice pattern formed by image edges; aligning the test image using the image edges to generate an aligned image including a second lattice pattern formed by aligned image edges; generating a compressed image by compressing the aligned image; and generating a quantified result by quantifying a per-pixel difference between the compressed image and the aligned image.

Abstract: Disclosed is a device for noise reduction using dual conversion gain, which includes an image sensor including a pixel array, the pixel array configured to generate a first pixel signal corresponding to a first conversion gain and a second pixel signal corresponding to a second conversion gain from pixels sharing a floating diffusion region and the image sensor configured to generate first image data and second image data based on the first pixel signal and the second pixel signal, and an image signal processor that generates an output image based on the first image data and the second image data. The image signal processor includes a normalization circuit that normalizes the first image data based on a dynamic range of the second image data to generate third image data, and a blending circuit that generates the output image based on the second image data and the third image data.

Abstract: An image sensor including an image signal processor and an operating method of the image sensor are provided. An image sensor may include a pixel array configured to convert a received optical signal into electrical signals, a readout circuit configured to analog-digital convert the electrical signals to generate image data, and an image signal processor configured to perform one-dimensional filtering in each of a first direction and a second direction on the image data to remove noise of the image data, the second direction being different than the first direction.

Abstract: An image processing device includes an image sensor including a pixel array that includes a first pixel group, and a correlated double sampling circuit. The first pixel group includes a first plurality of normal pixels, a second plurality of normal pixels, and at least one first phase detection pixel. The correlated double sampling circuit is configured to generate first video data, based on charges of the first plurality of normal pixels, generate second video data, based on charges of the second plurality of normal pixels, and generate first phase detection data, based on an output of the at least one first phase detection pixel. The image processing device further includes an image signal processor configured to apply a first weight to the generated first video data, and apply a second weight to the generated second video data.

Abstract: An electronic device includes a frequency analyzing circuit and a color difference calculating circuit. The frequency analyzing circuit receives an image signal including information about a subject, may convert the image signal into first color data which are based on a first color domain, converts the first color data into frequency data which are based on a frequency domain, and applies frequency weights corresponding to the frequency data to the first color data to generate processed color data. The color difference calculating circuit calculates color difference values for evaluating a color stain generated by the image signal, based on the processed color data. The frequency weights are selected based on sensitivity information of an observer according to a frequency change of the frequency data.