Abstract: Embodiments relate to circuitry for performing fusion of two images captured with two different exposure times to generate a fused image having a higher dynamic range. Information about first keypoints is extracted from the first image by processing pixel values of pixels in the first image. A model describing correspondence between the first image and the second image is then built by processing at least the information about first keypoints. A processed version of the first image is warped using mapping information in the model to generate a warped version of the first image spatially more aligned to the second image than to the first image. The warped version of the first image is fused with a processed version of the second image to generate the fused image.

Abstract: Embodiments relate to image signal processors (ISP) that include binner circuits that down-sample an input image. An input image may include a plurality of pixels. The output image of the binner circuit may include a reduced number of pixels. The binner circuit may include a plurality of different operation modes. In a bin mode, the binner circuit may blend a subset of input pixel values to generate an output pixel quad. In a skip mode, the binner circuit may select one of the input pixel values as the output pixel pixel. The selection may be performed randomly to avoid aliasing. In a luminance mode, the binner circuit may take a weighted average of a subset of pixel values having different colors. In a color value mode, the binner circuit may select one of the colors in a subset of pixel values as an output pixel value.

Abstract: Embodiments relate to image signal processors (ISP) that include one or more auto-focus circuits. Each of the auto-focus circuits may be connected to an image sensor and may be separate from a statistics circuit and other image processing pipelines of the ISP. An image sensor may include one or more focus pixels that are used to generate data for auto-focusing. The auto-focus circuit may extract the focus pixel values and generate a signal to control the lens position of the image sensor. Each image sensor may include a separate auto-focus circuit. When other image processing pipelines of the ISP are processing the image data from one image sensor, the auto-focus circuit for another image sensor may continue to generate focus signals that control the lens position of the other image sensor. The other image sensor may be in standby but may continue to remain in focus.

Abstract: Embodiments relate to circuitry for performing fusion of two images captured with two different exposure times to generate a fused image having a higher dynamic range. Information about first keypoints is extracted from the first image by processing pixel values of pixels in the first image. A model describing correspondence between the first image and the second image is then built by processing at least the information about first keypoints. A processed version of the first image is warped using mapping information in the model to generate a warped version of the first image spatially more aligned to the second image than to the first image. The warped version of the first image is fused with a processed version of the second image to generate the fused image.

Abstract: An image processing pipeline may dynamically determine filtering strengths for noise filtering of image data. Statistics may be collected for an image at an image processing pipeline. The statistics may be accessed and evaluated to generate a filter strength model that maps respective filtering strengths to different portions of the image. A noise filter may determine a filtering strength for image data received at the noise filter according to the filter strength model. The noise filter may then apply a filtering technique according to the determined filtering strength.

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: In an embodiment, an electronic device may be configured to capture still frames during video capture but may capture the still frames in the 4×3 aspect ratio and at higher resolution than the 16×9 aspect ratio video frames. The device may interleave high resolution, 4×3 frames and lower resolution 16×9 frames in the video sequence, and may capture the nearest higher resolution, 4×3 frame when the user indicates the capture of a still frame. Alternatively, the device may display 16×9 frames in the video sequence, and then expand to 4×3 frames when a shutter button is pressed. The device may capture the still frame and return to the 16×9 video frames responsive to a release of the shutter button.

Abstract: Embodiments of the present disclosure relate to autofocusing of images using motion vectors generated by an image signal processor of a device. An image being processed may include one or more motion detection windows associated with a motion vector as well as one or more autofocus windows. An autofocus window that follows a motion detection window by at least a threshold vertical distance may be selected, for example, to account for a period of time or latency for determining a motion vector of the motion detection window. The device may perform autofocusing by shifting location of the selected autofocus window.

Abstract: Embodiments of the present disclosure relate to autofocusing of images using motion vectors generated by an image signal processor of a device. An image being processed may include one or more motion detection windows associated with a motion vector as well as one or more autofocus windows. An autofocus window that follows a motion detection window by at least a threshold vertical distance may be selected, for example, to account for a period of time or latency for determining a motion vector of the motion detection window. The device may perform autofocusing by shifting location of the selected autofocus window.

Abstract: In an embodiment, an electronic device may be configured to capture still frames during video capture but may capture the still frames in the 4×3 aspect ratio and at higher resolution than the 16×9 aspect ratio video frames. The device may interleave high resolution, 4×3 frames and lower resolution 16×9 frames in the video sequence, and may capture the nearest higher resolution, 4×3 frame when the user indicates the capture of a still frame. Alternatively, the device may display 16×9 frames in the video sequence, and then expand to 4×3 frames when a shutter button is pressed. The device may capture the still frame and return to the 16×9 video frames responsive to a release of the shutter button.

Abstract: An image processing pipeline may perform temporal filtering on independent color channels in image data. A filter weight may be determined for a given pixel received at a temporal filter. The filter weight may be determined for blending a value of a channel in a full color encoding of the given pixel with a value of the same channel for a corresponding pixel in a previously filtered reference image frame. In some embodiments, the filtering strength for the channel may be determined independent from the filtering strength of another channel in the full color encoding of the given pixel. Spatial filtering may be applied to a filtered version of the given pixel prior to storing the given pixel as part of a new reference image frame.

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: An image processing pipeline may dynamically determine filtering strengths for noise filtering of image data. Statistics may be collected for an image at an image processing pipeline. The statistics may be accessed and evaluated to generate a filter strength model that maps respective filtering strengths to different portions of the image. A noise filter may determine a filtering strength for image data received at the noise filter according to the filter strength model. The noise filter may then apply a filtering technique according to the determined filtering strength.

Abstract: Embodiments of the present disclosure relate to an apparatus for converting image data from a Bayer format image to a four-plane image format using two memory channels. An example apparatus includes an interface for receiving the Bayer image including repeating pixel groups, where each pixel group includes a first pixel type, a second pixel type, a third pixel type, and a fourth pixel type. The apparatus also includes a memory and a circuit to write the Bayer image to the memory as four-plane data. The four-plane data includes pixels of the first type and the third type in the Bayer image that are written via the first memory channel, and pixels of the second type and the fourth type in the Bayer image that are written via the second memory channel. Embodiments also relate to converting three sensor image data to a Bayer format image using the two memory channels.

Abstract: Systems and methods for automatic lens flare compensation may include a non-uniformity detector configured to operate on pixel data for an image in an image sensor color pattern. The non-uniformity detector may detect a non-uniformity in the pixel data in a color channel of the image sensor color pattern. The non-uniformity detector may generate output including location and magnitude values of the non-uniformity. A lens flare detector may determine, based at least on the location and magnitude values, whether the output of the non-uniformity detector corresponds to a lens flare in the image. In some embodiments, the lens flare detector may generate, in response to determining that the output corresponds to the lens flare, a representative map of the lens flare. A lens flare corrector may determine one or more pixel data correction values corresponding to the lens flare and apply the pixel data correction values to the pixel data.

Abstract: An image processing pipeline may dynamically determine filtering strengths for noise filtering of image data. Statistics may be collected for an image at an image processing pipeline. The statistics may be accessed and evaluated to generate a filter strength model that maps respective filtering strengths to different portions of the image. A noise filter may determine a filtering strength for image data received at the noise filter according to the filter strength model. The noise filter may then apply a filtering technique according to the determined filtering strength.

Abstract: Embodiments of the present disclosure relate to performing noise reduction on an input image by first filtering the input image based on coarse noise models of pixels and then subsequently filtering the filtered input image based on finer noise models. The finer noise models use the same or more number of neighboring pixels than the coarse noise filters. The first filtering and subsequent filtering of a pixel in the input image use Mahalanobis distances between the pixel and its neighboring pixels. By performing iterations of filtering using more refined noise models, the noise reduction in the input image can be performed more efficiently and effectively.

Abstract: A pedestal level for an image sensor can be dynamically adjusted based on one or more parameters. The parameters include one or more operating conditions associated with the image sensor, pre-determined image sensor characterization data, the number of unused digital codes, and/or the number of clipped pixel signals. The operating conditions can include the temperature of the image sensor, the gain of at least one amplifier included in processing circuitry operably connected to at least one pixel, and/or the length of the integration period for at least one pixel in the image sensor. Based on the one or more of the parameters, the pedestal level is adjusted to reduce a number of unused digital codes in a distribution of dark current. Additionally or alternatively, the variance of the pixel signals can be reduced to permit the use of a lower pedestal level.

Abstract: Camera modules that may be dynamically adjusted during capture of an image. The camera may include a sensor that captures images using line scan imaging or other scanning technologies. A controller may dynamically control adjustment or movement of the camera lens by an actuator as an image is scanned by the sensor. The lens may be controlled to be in different positions and in different orientations in relation to the sensor as different lines or areas of pixels of the sensor are read. When capturing an image, a region of the sensor may be read, the lens may be adjusted, and a next region of the sensor may be read according to a pattern. Different focus, depth of field, perspective, and other effects may be achieved at different areas or regions of the image during image capture.

Abstract: In an embodiment, an electronic device may be configured to capture still frames during video capture but may capture the still frames in the 4×3 aspect ratio and at higher resolution than the 16×9 aspect ratio video frames. The device may interleave high resolution, 4×3 frames and lower resolution 16×9 frames in the video sequence, and may capture the nearest higher resolution, 4×3 frame when the user indicates the capture of a still frame. Alternatively, the device may display 16×9 frames in the video sequence, and then expand to 4×3 frames when a shutter button is pressed. The device may capture the still frame and return to the 16×9 video frames responsive to a release of the shutter button.