Abstract:
Embodiments relate to a multi-mode demosaicing circuit able to receive and demosaic image data in a different raw image formats, such as Bayer raw image format and Quad Bayer raw image format. The multi-mode demosaicing circuit demosaics Quad Bayer image data by interpolating a green channel of the image data along each of a plurality of directions, generating a gradient of the image data along each of the plurality of directions, modifying the interpolated green channels based on respective gradients to generate full-resolution green channel image data, which is combined with red and blue image data to generate the demosaiced image data. Interpolation is performed for non-green pixels based on neighboring green pixels along a specified direction, modified by a residual value based upon values of one or more nearby same-color pixels and a correlation between values of the same-color pixels and neighboring green pixels.
Abstract:
Embodiments relate to a multi-mode demosaicing circuit able to receive and demosaic image data in a different raw image formats, such as Bayer raw image format and Quad Bayer raw image format. The multi-mode demosaicing circuit comprises different circuitry for demosaicing different image formats that access a shared working memory. In addition, the multi-mode demosaicing circuit shares memory with a post-processing and scaling circuit configured to perform subsequent post-processing and/or scaling of the demosaiced image data, in which the operations of the post-processing and scaling circuit are modified based on the original raw image format of the demosaiced image data to use different amounts of the shared memory, to compensate for additional memory utilized by the multi-mode demosaicing circuit when demosaicing certain types of image data.
Abstract:
A foveated down sampling (FDS) circuit for down sampling of pixels in images. The FDS circuit down samples a first subset of pixels of a same color in an image using first scaling factors to generate first down sampled pixels in a first down sampled version of the image. The FDS circuit further down samples a second subset of the first down sampled pixels of the same color using second scaling factors to generate second down sampled pixels of the same color in a second down sampled version of the image. Pixels from the first subset are arranged in a first direction, and pixels from the second subset are arranged in a second direction.
Abstract:
In one implementation, a method includes obtaining an image. The method includes splitting the image to produce a high-frequency component image and a low-frequency component image. The method includes downsampling the low-frequency component image to generate a downsampled low-frequency component image. The method includes correcting color aberration of the downsampled low-frequency component image to generate a color-corrected downsampled low-frequency component image. The method includes upsampling the color-corrected downsampled low-frequency component image to generate a color-corrected low-frequency component image. The method includes combining the color-corrected low-frequency component image and the high-frequency component image to generate a color-corrected version of the image.
Abstract:
Embodiments relate to correcting pixels of images captured using a quadra image sensor. A defect detection circuit analyzes the pixels in the captured image and determines whether a pixel is defective. The defect detection circuit generates a first defect indication by determining whether pixel data of a pixel under test is brighter or darker by a first threshold value than pixel data of pixels in pixel tiles surrounding the pixel tile corresponding to the pixel under test. Moreover, the defect detection circuit generates a second defect indication by determining whether pixel data of the pixel under test is brighter or darker by a second threshold value than pixel data of other pixels in the pixel tile corresponding to the pixel under test. Using the first and second defect indications, the defect detection circuit identifies whether the pixel data of the pixel under test is defective.
Abstract:
Embodiments relate to axial chromatic aberration (ACA) reduction of raw image data generated by image sensors. A chromatic aberration reduction circuit performs chromatic aberration reduction on the raw image data to correct the ACA in the full color images through sharpening that has been clamped to reduce sharpening overshoot.
Abstract:
Embodiments relate to axial chromatic aberration (ACA) reduction of raw image data generated by image sensors. A chromatic aberration reduction circuit performs chromatic aberration reduction on the raw image data to correct the ACA in the full color images through sharpening that has been clamped to reduce sharpening overshoot.
Abstract:
Embodiments relate to a pixel defect detection circuit for detecting and correcting defective pixels in captured image frames. The pixel defect detection circuit includes a defect pixel location table that maps pixel locations in an image frame to respective confidence values, each confidence value indicating a likelihood that a corresponding pixel is defective. The pixel defect detection circuit further includes a dynamic defect processing circuit configured to determine whether a first pixel of an image frame is defective, and a flatness detection circuit configured to determine whether the first pixel is in a flat region of the image frame. The confidence value corresponding to the location of the first pixel is updated based upon whether the first pixel is determined be defective if the first pixel is determined to be in a flat region, and not updated if the first pixel is determined to not be in a flat region.
Abstract:
An image signal processor may include a pixel defect correction component that tracks defect history for frames captured by an image sensor and applies the history when identifying and correcting defective pixels in a frame. The component maintains a defect pixel location table that includes a defect confidence value for pixels of the image sensor. The component identifies defective pixels in a frame, for example by comparing each pixel's value to the values of its neighbor pixels. If a pixel is detected as defective, its defect confidence value may be incremented. Otherwise, the value may be decremented. If a pixel's defect confidence value is over a defect confidence threshold, the pixel is considered defective and thus may be corrected. If a pixel's defect confidence value is under the threshold, the pixel is considered not defective and thus may not be corrected even if the pixel was detected as defective.
Abstract:
A temporal filter may perform dynamic motion estimation and compensation for filtering an image frame. A row of pixels in an image frame received for processing at the temporal filter may be received. A motion estimate may be dynamically determined that registers a previously filtered reference image frame with respect to the row of pixels in the image frame. The reference image frame may be aligned according to the determined motion estimate, and pixels in the row of the image frame may be blended with corresponding pixels in the aligned reference image frame to generate a filtered version of the image frame. Motion statistics may be collected for subsequent processing based on the motion estimation and alignment for the row of pixels in the image frame.