In a case where illuminance is high, an error between the number of photons per frame calculated from time information and the number of photons and the actually expected number of photons per frame is reduced. In a time counter that counts a clock from the start of exposure in one frame, one-count time in the clock is switched depending on the illuminance. In a case where a pixel counter is saturated within a period of one frame, the illuminance is determined to be high, and a high-illuminance clock in which one-count time is set more minutely in the first half of one frame is used to count. In a case where the illuminance is not determined to be high, a normal clock is used to count.

In a case where illuminance is high, an error between the number of photons per frame calculated from time information and the number of photons and the actually expected number of photons per frame is reduced. In a time counter that counts a clock from the start of exposure in one frame, one-count time in the clock is switched depending on the illuminance. In a case where a pixel counter is saturated within a period of one frame, the illuminance is determined to be high, and a high-illuminance clock in which one-count time is set more minutely in the first half of one frame is used to count. In a case where the illuminance is not determined to be high, a normal clock is used to count.

An operating method of an imaging device comprising a plurality of shared pixels that share a floating diffusion node and each comprising sub-pixels covered by a micro-lens. The method involves generating a capture image from the plurality of shared pixels that receive light reflected from an object; compensating for the capture image using static phase information based on misalignment of the micro lens of each of the plurality of shared pixels; performing auto exposure control based on the compensation of the capture image; performing auto focus control based on the compensated capture image; and generating an output image by processing the compensated capture image.

An image sensor includes a plurality of pixels, where each of the plurality of pixels includes a photodiode. The image sensor is configured to capture images of a scene exposed with a flickering light source by for each of the plurality of pixels, acquiring a value representative of a light level at a corresponding pixel by gradually varying a value of sensitivity of the corresponding pixel.

The image sensor pixel may include a photodiode, a charge storage region, readout circuitry, and a transfer transistor that couples the photodiode to the charge storage region. The photodiode may generate first and second image signals during first and second exposure periods, respectively. The transfer transistor may transfer the first image signal to the charge storage region. While generating the second image signal, the readout circuitry may perform readout operations on the first image signal. Thereafter, the charge storage region may be reset to a reset voltage level. The readout circuitry may perform readout operations on the reset voltage level. Then, transfer transistor may transfer the second image signal to the charge storage region. The readout circuitry may perform readout operations on the second image signal. The readout operations on both the first and second image signals may be double sampling readouts.

There is provided an image processing device including a light sensor and a processor. The light sensor is used to detect light and output an image frame. The processor identifies intensity of ambient light according to an image parameter associated with the image frame. When the ambient light is identified to be strong enough, the processor performs an object identification directly using the image frame. When the ambient light is identified to be not enough, the processor firstly converts the image frame to a converted image using a machine learning model, and then performs the object identification using the converted image.

There is provided an image processing device including a light sensor and a processor. The light sensor is used to detect light and output an image frame. The processor identifies intensity of ambient light according to an image parameter associated with the image frame. When the ambient light is identified to be strong enough, the processor performs an object identification directly using the image frame. When the ambient light is identified to be not enough, the processor firstly converts the image frame to a converted image using a machine learning model, and then performs the object identification using the converted image.

Various embodiments of the present technology may comprise a method and apparatus for a pixel array. Each pixel may include multiple storage regions capable of storing pixel signals during integration. The method and apparatus may utilize the floating diffusion region as a storage region during both an integration period and readout period. The method and apparatus may store pixel signals corresponding to a first exposure periods in the floating diffusion region and pixel signals corresponding to a second exposure periods in a separate storage region.

This disclosure provides systems, methods, and devices for image processing that supports high dynamic range (HDR) photography. In some aspects, a method of generating a full-resolution HDR photograph with in-sensor zoom includes receiving first and second image data corresponding to first and second exposure captures of a scene. First and second full-resolution image frames may be generated from the first and second image data, which are subsequently processed with HDR fusion to obtain an output image frame with higher dynamic range than either the first or second image data. The first full-resolution image frame may be determined from both the first and second image data by compensating the second image data for differences between the first and second exposures. Other aspects and features are also claimed and described.

This disclosure provides systems, methods, and devices for image processing that supports high dynamic range (HDR) photography. In some aspects, a method of generating a full-resolution HDR photograph with in-sensor zoom includes receiving first and second image data corresponding to first and second exposure captures of a scene. First and second full-resolution image frames may be generated from the first and second image data, which are subsequently processed with HDR fusion to obtain an output image frame with higher dynamic range than either the first or second image data. The first full-resolution image frame may be determined from both the first and second image data by compensating the second image data for differences between the first and second exposures. Other aspects and features are also claimed and described.