Abstract:
The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may detect and correct a defective pixel of image data acquired using an image sensor. The image processing pipeline may receive an input pixel of the image data acquired using the image sensor. The image processing pipeline may then identify a set of neighboring pixels having the same color component as the input pixel and remove two neighboring pixels from the set of neighboring pixels thereby generating a modified set of neighboring pixels. Here, the two neighboring pixels correspond to a maximum pixel value and a minimum pixel value of the set of neighboring pixels. The image processing pipeline may then determine a gradient for each neighboring pixel in the modified set of neighboring pixels and determine whether the input pixel includes a dynamic defect or a speckle based at least in part on the gradient for each neighboring pixel in the modified set of neighboring pixels.
Abstract:
Systems and methods for correcting green channel non-uniformity (GNU) are provided. In one example, GNU may be corrected using energies between the two green channels (Gb and Gr) during green interpolation processes for red and green pixels. Accordingly, the processes may be efficiently employed through implementation using demosaic logic hardware. In addition, the green values may be corrected based on low-pass-filtered values of the green pixels (Gb and Gr). Additionally, green post-processing may provide some defective pixel correction on interpolated greens by correcting artifacts generated through enhancement algorithms.
Abstract:
Systems and methods for correcting green channel non-uniformity (GNU) are provided. In one example, GNU may be corrected using energies between the two green channels (Gb and Gr) during green interpolation processes for red and green pixels. Accordingly, the processes may be efficiently employed through implementation using demosaic logic hardware. In addition, the green values may be corrected based on low-pass-filtered values of the green pixels (Gb and Gr). Additionally, green post-processing may provide some defective pixel correction on interpolated greens by correcting artifacts generated through enhancement algorithms.
Abstract:
Embodiments relate to a front-end scaler circuit configured to receive and process demosaiced image data in different modes depending on if the demosaiced image data was demosaiced from Bayer or Quad Bayer raw image data. The front-end scaler circuit shares memory with a demosaicing circuit, and is configured to perform different operations that use different amounts of the shared memory based on the original image format of the demosaiced image data being processed, to compensate for additional memory utilized by the demosaicing circuit when demosaicing certain types of image data. For example, when processing image data demosaiced from Quad Bayer image data, the front-end scaler circuit discards a portion of the chrominance component data for the received image data before performing chromatic suppression, compared to when processing image data demosaiced from Bayer image data.
Abstract:
The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may be configured to receive a frame of the image data having a plurality of pixels acquired using a digital image sensor. The image processing pipeline may then be configured to determine a first plurality of correction factors that may correct each pixel in the plurality of pixels for fixed pattern noise. The first plurality of correction factors may be determined based at least in part on fixed pattern noise statistics that correspond to the frame of the image data. After determining the first plurality of correction factors, the image processing pipeline may be configured to apply the first plurality of correction factors to the plurality of pixels, thereby reducing the fixed pattern noise present in the plurality of pixels.
Abstract:
Embodiments relate to an image processing circuit comprising a noise reduction circuit configurable to perform bilateral filtering on demosaiced and resampled image data, or on raw image data, based on the operating mode of the image processing circuit. The noise reduction circuit filters received image data based upon directional taps, by selecting, for each pixel, a set of neighbor pixels, and comparing values of the set of neighbor pixels to determine whether the pixel lies on a directional edge. For raw images, the noise reduction circuit selects the set of neighbor pixels to include a plurality of pixels of the same color channel as the pixel, and one or more additional pixels of a different color channel, where color values for the one or more additional pixels are determined by interpolating color values of two or more adjacent pixels of the same color channel as the pixel.
Abstract:
The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may be configured to receive a frame of the image data having a plurality of pixels acquired using a digital image sensor. The image processing pipeline may then be configured to determine a first plurality of correction factors that may correct each pixel in the plurality of pixels for fixed pattern noise. The first plurality of correction factors may be determined based at least in part on fixed pattern noise statistics that correspond to the frame of the image data. After determining the first plurality of correction factors, the image processing pipeline may be configured to configured to apply the first plurality of correction factors to the plurality of pixels, thereby reducing the fixed pattern noise present in the plurality of pixels.
Abstract:
A foveated down sampling and correction (FDS-C) circuit for combined down sampling and correction of chromatic aberrations in images. The FDS-C circuit performs down sampling and interpolation of pixel values of a first subset of pixels of a color in a raw image using down sampling scale factors and first interpolation coefficients to generate first corrected pixel values for pixels of the color in a first corrected version of the raw image. The FDS-C circuit further performs interpolation of pixel values of a second subset of the pixels in the first corrected version using second interpolation coefficients to generate second corrected pixel values for pixels of the color in a second corrected version of the raw image. Pixels in the first subset are arranged in a first direction, pixels in the second subset are arranged in a second direction, and the down sampling scale factors vary along the first direction.
Abstract:
Embodiments relate to processing of pixels captured by a quadra image sensor. A quadra image sensor includes a plurality of pixel tiles, each having a plurality of pixels corresponding to the same color. A lens shading correction (LSC) circuit receives, for each of a plurality of colors, a set of gain tables. Each gain table corresponds to a different channel associated with the color. Each gain table includes a set of gain values, each associated with a location. The LSC circuit determines a pixel gain value for each pixel in a pixel tile and scales the pixels in the pixel tile based on the determined pixel gain values.
Abstract:
The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may be configured to receive a frame of the image data having a plurality of pixels acquired using a digital image sensor. The image processing pipeline may then be configured to determine a first plurality of correction factors that may correct each pixel in the plurality of pixels for fixed pattern noise. The first plurality of correction factors may be determined based at least in part on fixed pattern noise statistics that correspond to the frame of the image data. After determining the first plurality of correction factors, the image processing pipeline may be configured to configured to apply the first plurality of correction factors to the plurality of pixels, thereby reducing the fixed pattern noise present in the plurality of pixels.