In some implementations, a method includes: determining a complexity value for first image data associated with of a physical environment that corresponds to a first time period; determining an estimated composite setup time based on the complexity value for the first image data and virtual content for compositing with the first image data; in accordance with a determination that the estimated composite setup time exceeds the threshold time: forgoing rendering the virtual content from the perspective that corresponds to the camera pose of the device relative to the physical environment during the first time period; and compositing a previous render of the virtual content for a previous time period with the first image data to generate the graphical environment for the first time period.

The present disclosure describes devices and methods for generating RGB images from Bayer filter images using adaptive sub-pixel spatiotemporal interpolation. An electronic device includes a processor configured to estimate green values at red and blue pixel locations of an input Bayer frame based on green values at green pixel locations of the input Bayer frame and a kernel for green pixels, generate a green channel of a joint demosaiced-warped output RGB pixel from the input Bayer frame based on the green values at the green pixel locations, the kernel for green pixels, and an alignment vector map, and generate red and blue channels of the joint demosaiced-warped output RGB pixel from the input Bayer frame based on the estimated green values at the red and blue pixel locations, kernels for red and blue pixels, and the alignment vector map.

A transformer may transform image data from a first color pattern to a second color pattern. The transforming of image data may be applied to image data received from a memory storing an array of intensities corresponding to a first color pattern of a first color filter array (CFA) of an image sensor to a second color pattern. The second color pattern may be a color pattern of a size smaller that the first CFA. Remosaicing may be applied to the second color pattern to obtain image data organized in a Bayer color pattern. The transforming may be configured to operate on data from an image sensor to obtain different zoom levels not available without applying a digital zoom algorithm that involve upscaling, which reduces the image quality of the image data.

There is provided with an image processing apparatus. A noise reduction unit generates a noise-reduced image in which noise is reduced from an input image in which a plurality of types of pixels that represent mutually different types of color information are arranged in one plane. An extraction unit generates a high-frequency emphasized image in which a high-frequency component of the input image is emphasized. A demosaicing unit generates a demosaiced image having a plurality of planes that each represent one type of color information by demosaicing processing to the noise-reduced image. A generation unit generates an output image by correcting the demosaiced image by using the high-frequency emphasized image.

An image is received from a camera built into a cabin of a vehicle. The image is demosaiced and its noise is reduced. A segmentation algorithm is applied to the image. A global illumination for the image is solved. Based on the segmentation of the image and the global illumination, a bidirectional reflectance distribution function (BRDF) for color and/or reflectance information of material in the cabin area of the vehicle is solved for. A white balance matrix and a color correction matrix for the image are computed based on the BRDF. The white balance matrix and the color correction matrix are applied to the image, which is then displayed or stored for addition image processing.

An image processing device includes a memory, and a processor configured to execute obtaining image data from an imaging device in which pixel groups of multiple colors are repeatedly arranged, each of the pixel groups including multiple pixels; and determining a direction in which change in a pixel value is small at a position of a target pixel group, based on a changed amount of the pixel values of at least one of pairs of pixels that are arranged around the target pixel group, and included in multiple other pixel groups having colors that are different from a color of the target pixel group.

A facial verification method includes separating a query face image into color channel images of different color channels, obtaining a multi-color channel target face image with a reduced shading of the query face image based on a smoothed image and a gradient image of each of the color channel images, extracting a face feature from the multi-color channel target face image, and determining whether face verification is successful based on the extracted face feature.

A first image acquisition unit acquires a first image that is captured by a sensor having a first pixel arrangement pattern and includes a first reproduction band in a frequency domain. A second image acquisition unit acquires a second image that is captured by a sensor having a second pixel arrangement pattern and includes a second reproduction band different from the first reproduction band in the frequency domain. A correction processing unit generates a first correction image by correction processing of at least reducing or deleting high-frequency components that are not included in the second reproduction band within the first reproduction band.

An electronic device may include enhancement circuitry to enhance high resolution image data to improve perceived quality of an image corresponding to the high resolution image data. The enhancement circuitry may include tone detection circuitry to determine one or more tones within the image and apply changes to the high resolution image data based on the one or more tones. The enhancement circuitry may also include example-based improvement circuitry to compare the high resolution image data to low resolution image data and apply changes to the high resolution image data based on differences between sections of the high resolution image data and sections of the low resolution image data. The enhancement circuitry may also include channel processing circuitry to apply the first and second changes to one or more channels of the high resolution image data.

In one embodiment, a method includes obtaining an image comprising a plurality of pixels, determining, for a particular pixel of the plurality of pixels, a gradient value, classifying, based on the gradient value, the particular pixel into a flat class or one of a plurality of edge classes, and denoising the particular pixel based on the classification.