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 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: 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 processing pipeline may apply chroma suppression to image data at a scaler implemented in the image processing pipeline. Image data collected for an image may be received at a scaler that is encoded in a color space that includes a luminance component and chrominance components. When resampling the image data to generate a different size of the image, the scaler may attenuate the chrominance components of the image data according to the luminance component of the image data. The scaler may also perform dot error correction and convert the image data from one subsampling scheme to another.

Abstract: An image processing pipeline may process image data at multiple rates. A stream of raw pixel data collected from an image sensor for an image frame may be processed through one or more pipeline stages of an image signal processor. The stream of raw pixel data may then be converted into a full-color domain and scaled to a data size that is less than an initial data size for the image frame. The converted pixel data may be processed through one or more other pipelines stages and output for storage, further processing, or display. In some embodiments, a back-end interface may be implemented as part of the image signal processor via which image data collected from sources other than the image sensor may be received and processed through various pipeline stages at the image signal processor.

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: In-stream rolling shutter compensation may be utilized to modify image data to compensate for detected camera motion. An image processor may perform motion matching on image data received from a camera sensor to determine whether and how the camera is moving. Strips of image data are analyzed to find matching locations between the current image and a previous image by generating graphical profiles for each image strip. The graphical profiles for the current strip are compared to corresponding profiles from the previous image to determine matching locations between the two frames. A motion vector for the strip may be computed based on spatial distances between the match locations of the current image and corresponding match locations of the previous frame. Image data for the current strip may be modified based on the motion vector to compensate for perceived camera motion as it is written out to memory.

Abstract: A temporal filter in an image processing pipeline may perform filtering using spatial filtering and noise history. A given pixel of a current image frame may be received for filtering at a temporal filter. A filtering weight may be determined for blending the given pixel with a corresponding pixel of a reference image frame that was previously filtered at the temporal filter. The filtering weight may be determined based on neighboring pixels of the given pixel in the current image frame and corresponding pixels in the reference image frame. The filtering weight may be adjusted according to a quality score indicating noise history for the corresponding pixel in the reference image frame. Based on the filtering weight, a filtered version of the given pixel may be generated, blending the given pixel and the corresponding pixel to store as part of a filtered version of the current image frame.

Abstract: A temporal filter in an image processing pipeline may be configured to generate a high dynamic range (HDR) image. Image frames captured to generate an HDR image frame be blended together at a temporal filter. An image frame that is part of a group of image frames capture to generate the HDR image may be received for filtering at the temporal filter module. A reference image frame, which may be a previously filtered image frame or an unfiltered image frame may be obtained. A filtered version of the image frame may then be generated according to an HDR blending scheme that blends the reference image frame with the image frame. If the image frame is the last image frame of the group of image frames to be filtered, then the filtered version of the image frame may be provided as the HDR image frame.

Abstract: An image signal processor of a device, apparatus, or computing system that includes a camera capable of capturing image data may apply piecewise perspective transformations to image data received from the camera's image sensor. A scaling unit of an Image Signal Processor (ISP) may perform piecewise perspective transformations on a captured image to correct for rolling shutter artifacts and to provide video image stabilization. Image data may be divided into a series of horizontal slices and perspective transformations may be applied to each slice. The transformations may be based on motion data determined in any of various manners, such as by using gyroscopic data and/or optical-flow calculations. The piecewise perspective transforms may be encoded as Digital Difference Analyzer (DDA) steppers and may be implemented using separable scalar operations. The image signal processor may not write the received image data to system memory until after the transformations have been performed.

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.

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: A temporal filter in an image processing pipeline may insert a frame delay when filtering an image frame. A given pixel of a current image frame may be received and a filtered version of the given pixel may be generated, blending the given pixel and a corresponding pixel of a reference image frame to store as part of a filtered version of the current image frame. If a frame delay setting is enabled, the corresponding pixel of the reference image frame may be provided as output for subsequent image processing inserting a frame delay for the current image frame. During the frame delay programming instructions may be received and image processing pipeline components may be configured according to the programming instructions. If the frame delay setting is disabled, then the filtered version of the given pixel may be provided as output for subsequent image processing.

Abstract: Image tone adjustment using local tone curve computation may be utilized to adjust luminance ranges for images. Image tone adjustment using local tone curve computation may reduce the overall contrast of an image, while maintaining local contrast in smaller areas, such as in images capturing brightly lit scenes where the difference in intensity between brightest and darkest areas is large. A desired brightness representation of the image may be generated including target luminance values for corresponding blocks of the image. For each block, one or more tone adjustment values may be computed, that when jointly applied to the respective histograms for the block and neighboring blocks results in the luminance values that match corresponding target values. The tone adjustment values may be determined by solving an under-constrained optimization problem such that optimization constraints are minimized. The image may then be adjusted according to the computed tone adjustment values.

Abstract: Systems and methods are provided for selectively performing image statistics processing based at least partly on whether a pixel has been clipped. In one example, an image signal processor may include statistics collection logic. The statistics collection logic may include statistics image processing logic and a statistics core. The statistics image processing logic may perform initial image processing on image pixels, at least occasionally causing some of the image pixels to become clipped. The statistics core may obtain image statistics from the image pixels. The statistics core may obtain at least one of the image statistics using only pixels that have not been clipped and excluding pixels that have been clipped.

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: Systems and methods for processing image data in RGB format are provided. In one example, an electronic device includes memory to store image data in raw or RGB format, or both, and an RGB image processing pipeline to process the image data. Specifically, the RGB image processing pipeline may process the image data regardless of whether the image data is of raw or RGB format. The RGB image processing pipeline may include receiving logic to receive the image data in raw or RGB format and demosaicing logic to, when the receiving logic receives the image data in raw format, convert the image data into RGB format. The logic may include local tone mapping logic configured to apply spatially varying tone curves to the image data, a color correction matrix configured to correct color in the image data, and gamma logic configured to transform the image data into gamma space.

Abstract: An input rescale module that performs cross-color correlated downscaling of sensor data in the horizontal and vertical dimensions. The module may perform a first-pass demosaic of sensor data, apply horizontal and vertical scalers to resample and downsize the data in the horizontal and vertical dimensions, and then remosaic the data to provide horizontally and vertically downscaled sensor data as output for additional image processing. The module may, for example, act as a front end scaler for an image signal processor (ISP). The demosaic performed by the module may be a relatively simple demosaic, for example a demosaic function that works on 3×3 blocks of pixels. The front end of module may receive and process sensor data at two pixels per clock (ppc); the horizontal filter component reduces the sensor data down to one ppc for downstream components of the input rescale module and for the ISP pipeline.

Abstract: A temporal filter in an image processing pipeline may perform filtering using spatial filtering and noise history. A given pixel of a current image frame may be received for filtering at a temporal filter. A filtering weight may be determined for blending the given pixel with a corresponding pixel of a reference image frame that was previously filtered at the temporal filter. The filtering weight may be determined based on neighboring pixels of the given pixel in the current image frame and corresponding pixels in the reference image frame. The filtering weight may be adjusted according to a quality score indicating noise history for the corresponding pixel in the reference image frame. Based on the filtering weight, a filtered version of the given pixel may be generated, blending the given pixel and the corresponding pixel to store as part of a filtered version of the current image frame.