Abstract: A method includes obtaining a raw image and mapping, using a raw image encoder, the raw image to a compressed domain. The raw image is represented using latent variables in the compressed domain. The method also includes performing one or more image signal processing operations on the latent variables, where (i) each of the one or more image signal processing operations is configured to operate in the compressed domain and (ii) the one or more image signal processing operations generate processed latent variables. The method further includes mapping, using an output image decoder, the processed latent variables to an output image in an output color space.

Abstract: A method includes downsampling an input frame and performing global contrast enhancement of the input frame based on the downsampled input frame to generate a globally contrast-enhanced frame. The method also includes generating texture maps at different scale resolutions based on the downsampled input frame. The method further includes generating clipped histograms at the different scale resolutions based on the downsampled input frame. The method also includes generating lookup tables (LUTs) at the different scale resolutions based on the texture maps and the clipped histograms. The method further includes applying the LUTs at the different scale resolutions to the input frame in order to generate locally contrast-enhanced frames. In addition, the method includes blending the locally contrast-enhanced frames and the globally contrast-enhanced frame to generate an output frame.

Abstract: 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. The processor is also configured to generate red, green, and blue channels of joint demosaiced-warped output RGB pixels from the input Bayer frame based on the green values at the green pixel locations, the estimated green values at the red and blue pixel locations, an alignment vector map, and kernels for red, green, and blue pixels.

Abstract: A method for dynamic calibration correction in multi-frame, multi-exposure capture in a camera system includes receiving an amplified non-reference frame (e.g., with non-standard exposure value EV-4) to which a digital gain was applied and a reference frame (e.g., with standard exposure value EV0). The method includes generating a mask based on the reference frame and the amplified non-reference frame. The method includes estimating a scaling coefficient and an offset coefficient for each of a number of channels in the amplified non-reference frame, based on selected pixel locations in the generated mask. The method includes correcting a calibration of the amplified non-reference frame by applying the scaling coefficients for each of the channels. The method also includes outputting a calibration-corrected amplified non-reference frame to a multi-frame processor.

Abstract: A method includes obtaining a reference image frame and a non-reference image frame and generating a mask based on the reference image frame and the non-reference image frame. The method also includes determining a scaling coefficient and an offset coefficient for each of multiple color channels of the non-reference image frame based on pixels in the reference image frame and pixels in the non-reference image frame that are identified by the mask. The method further includes applying the scaling and offset coefficients to the non-reference image frame in order to generate a calibration-corrected non-reference image frame.

Abstract: 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. The processor is also configured to generate red, green, and blue channels of joint demosaiced-warped output RGB pixels from the input Bayer frame based on the green values at the green pixel locations, the estimated green values at the red and blue pixel locations, an alignment vector map, and kernels for red, green, and blue pixels.

Abstract: 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.

Abstract: An electronic device is provided. The electronic device includes a display, a camera module disposed under the display, and a processor electrically connected to the display and the camera module. The processor is configured to acquire a sample frame by using the camera module, identify whether a light source object is included in the sample frame, determine an imaging parameter for acquisition of first multiple frames when the light source object is identified to be included in the sample frame, acquire multiple frames, based on the imaging parameter, composite the multiple frames to generate a composite frame, identify an attribute of the light source object included in the composite frame, and perform frame correction of the composite frame, based on the identified attribute.

Abstract: 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.

Abstract: A method includes receiving a reference input frame and a non-reference input frame; separating a luma plane for a luma channel and a chroma plane for a chroma channel for each of the reference input frame and the non-reference input frame; generating a luma frame using the luma plane; generating a chroma frame using the chroma plane in a patch-based chroma blending; and combining the luma frame and the chroma frame into an output frame.

Abstract: A method for dynamic calibration correction in multi-frame, multi-exposure capture in a camera system includes receiving an amplified non-reference frame (e.g., with non-standard exposure value EV-4) to which a digital gain was applied and a reference frame (e.g., with standard exposure value EV0). The method includes generating a mask based on the reference frame and the amplified non-reference frame. The method includes estimating a scaling coefficient and an offset coefficient for each of a number of channels in the amplified non-reference frame, based on selected pixel locations in the generated mask. The method includes correcting a calibration of the amplified non-reference frame by applying the scaling coefficients for each of the channels. The method also includes outputting a calibration-corrected amplified non-reference frame to a multi-frame processor.

Abstract: A mobile hyperspectral camera system is described. The mobile hyperspectral camera system comprises a mobile host device comprising a processor and a display: a plurality of cameras, coupled to the processor, configured to capture images in distinct spectral bands; and a hyperspectral flash array, coupled to the processor, configured to provide illumination to the distinct spectral bands. A method of implementing a mobile hyperspectral camera system is also described.

Abstract: A method includes receiving a reference input frame and a non-reference input frame; separating a luma plane for a luma channel and a chroma plane for a chroma channel for each of the reference input frame and the non-reference input frame; generating a luma frame using the luma plane; generating a chroma frame using the chroma plane in a patch-based chroma blending; and combining the luma frame and the chroma frame into an output frame.

Abstract: A method of capturing a photo using a mobile device is described. The method comprises detecting a signature motion of the mobile device; capturing video using a camera of the mobile device upon detecting the signature motion; and automatically identifying a start frame and an end frame of the captured images using neural networks. A mobile device for capturing a photo is also described.

Abstract: A method of generating an image from multiple cameras having different focal lengths is described. The method comprising receiving a wide image and a tele image; aligning the wide image and the tele image to overlap a common field of view; correcting for photometric differences between the wide image and the tele image; selecting a stitching seam for the wide image and the tele image; and joining the wide image and the tele image to generate a composite image, wherein a first portion of the composite image on one side of the stitching seam is from the wide image and a second portion of the composite image on the other side of the stitching seam is from the tele image. An electronic device for generating an image is also described.

Abstract: A method of processing image data in a composite image is described. The method comprises analyzing a multi-level blending of images of the composite image; identifying sharp transition boundary areas of the composite image; applying less attenuation for higher levels of multi-level blending of the composite image in the sharp transition boundary areas; and applying more attenuation for lower levels of multi-level blending of the composite image in the sharp transition boundary areas.

Abstract: A method of synchronizing images from multiple image sensors having different properties is described. The method comprises synchronizing a capture of a first image using a first image sensor and a capture of a second image using a second image sensor; and storing at least one of (a) the captured first image on an on-sensor memory of the first image sensor, or (b) the captured second image on an on-sensor memory of the second image sensor.

Abstract: A method of combining content from multiple frames with overlapping field of views is described. The method comprises identifying corresponding blocks between a first frame and a second frame of an image; and determining whether to replace at least a portion of the first frame with a corresponding portion of the second frame based on whether there is a match between the first frame and the second frame.

Abstract: A method to enhance quality of an image comprises receiving the image; identifying a region of the image associated with an object in the image; applying first image processing for the object in the image; applying second image processing on the remaining portions of the image.

Abstract: A method of capturing a photo using a mobile device is described. The method comprises detecting a signature motion of the mobile device; capturing video using a camera of the mobile device upon detecting the signature motion; and automatically identifying a start frame and an end frame of the captured images using neural networks. A mobile device for capturing a photo is also described.