Abstract: A method for disparity estimation between digital images includes generating an interleaved image from two or more digital images with an offset between them, where the interleaved image is subdivided into a plurality of patches, computing discrete cosine transform (DCT) coefficients of each of the plurality of patches, computing, for each of the plurality of patches, a mean DCT descriptor from the DCT coefficients of each patch, and determining a disparity map from the mean DCT descriptor of each of the plurality of patches using a classifier. The disparity map is configured for real-time depth estimation from the two or more digital images.

Abstract: A method for detecting color moiré in an image, including: obtaining image data corresponding to an input image, wherein the image data comprises chrominance channel data and luminance channel data; applying a frequency transform to the image data to obtain transformed image data; based on the transformed image data, selecting at least one lowest frequency component in the chrominance channel data, and at least one lowest frequency component in the luminance channel data; determining a first magnitude corresponding to the at least one lowest frequency component in the chrominance channel data, and a second magnitude corresponding to the at least one lowest frequency component in the luminance channel data; determining a moiré grade by calculating a ratio of the first magnitude and the second magnitude; and detecting a color moiré artifact in the input image based on the moiré grade

Abstract: A method for disparity estimation between digital images includes generating an interleaved image from two or more digital images with an offset between them, where the interleaved image is subdivided into a plurality of patches, computing discrete cosine transform (DCT) coefficients of each of the plurality of patches, computing, for each of the plurality of patches, a mean DCT descriptor from the DCT coefficients of each patch, and determining a disparity map from the mean DCT descriptor of each of the plurality of patches using a classifier. The disparity map is configured for real-time depth estimation from the two or more digital images.

Abstract: A method of controlling power usage in an image signal processor includes measuring an actual percentage of flat pixels in a digital image, adjusting a percentage threshold of flat pixels in the digital image, based on the measured actual percentage of flat pixels in the digital image; and processing the digital image by the image signal processor based on the percentage threshold of flat pixels. The percentage threshold of flat pixels is adjusted to reduce power used by the image signal processor in processing the digital image.

Abstract: A method for down-up sampling of image sensor data includes the steps of down sampling green pixels in a super Bayer pattern of image sensor data, where a decimation factor of the downsampling corresponds to a size of a color cluster in the super Bayer pattern, where two green pixels that are those closest to a non-green pixel cluster remain in each green cluster after downsampling, and wherein each non-green pixel cluster is bordered by four downsampled green pixels, and up sampling non-green color pixels in a non-green cluster from the remaining green pixels that are closest to the non-green cluster by a bilinear interpolation of each non-green pixel with respect to the closest remaining green pixels, where the up sampling of the non-green color pixels is guided by a compressed array that corresponds to the image sensor data.

Abstract: A method for down-up sampling of image sensor data includes the steps of down sampling green pixels in a super Bayer pattern of image sensor data, where a decimation factor of the downsampling corresponds to a size of a color cluster in the super Bayer pattern, where two green pixels that are those closest to a non-green pixel cluster remain in each green cluster after downsampling, and wherein each non-green pixel cluster is bordered by four downsampled green pixels, and up sampling non-green color pixels in a non-green cluster from the remaining green pixels that are closest to the non-green cluster by a bilinear interpolation of each non-green pixel with respect to the closest remaining green pixels, where the up sampling of the non-green color pixels is guided by a compressed array that corresponds to the image sensor data.