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: Systems and methods may employ separate image sensors for collecting different types of data. In one embodiment, separate luma, chroma and 3-D image sensors may be used. The systems and methods may involve generating an alignment transform for the image sensors, and using the 3-D data from the 3-D image sensor to process disparity compensation. The systems and methods may involve image sensing, capture, processing, rendering and/or generating images. For example, one embodiment may provide an imaging system, including: a first image sensor configured to obtain luminance data of a scene; a second image sensor configured to obtain chrominance data of the scene; a third image sensor configured to obtain three-dimensional data of the scene; and an image processor configured to receive the luminance, chrominance and three-dimensional data and to generate a composite image corresponding to the scene from that data.

Abstract: Various techniques are disclosed for processing statistics data in an image signal processor (ISP). In one embodiment, a statistics collection engine may be configured to acquire statistics relating to auto white-balance. The statistics collection engine may receive raw Bayer RGB data acquired by an image sensor and may be configured to perform one or more color space conversions to obtain pixel data in other color spaces. A set of pixel filters may be configured to accumulate sums of the pixel data conditionally based upon YC1C2 characteristics, as defined by a pixel condition per pixel filter. Depending on a selected color space, the pixel filters may generate color sums, which may be used to match a current illuminant against a set of reference illuminants with which the image sensor has been previously calibrated.

Abstract: Systems and methods for processing YCC image data provided. In one example, an electronic device includes memory to store image data in RGB or YCC format and a YCC image processing pipeline to process the image data. The YCC image processing pipeline may include receiving logic configured to receive the image data in RGB or YCC format and color space conversion logic configured to, when the image data is received in RGB format, convert the image data into YCC format. The YCC image processing logic may also include luma sharpening and chroma suppression logic; brightness, contrast, and color adjustment logic; gamma logic; chroma decimation logic; scaling logic; and chromanoise reduction logic.

Abstract: Systems and methods for correcting geometric distortion are provided. In one example, an electronic device may include an imaging device, which may obtain image data of a first resolution, and geometric distortion and scaling logic. The imaging device may include a sensor and a lens that causes some geometric distortion in the image data. The geometric distortion correction and scaling logic may scale and correct for geometric distortion in the image data by determining first pixel coordinates in uncorrected or partially corrected image data that, when resampled, would produce corrected output image data at second pixel coordinates. The geometric distortion correction and scaling logic may resample pixels around the image data at the first pixel coordinates to obtain the corrected output image data at the second pixel coordinates. The corrected output image data may be of a second resolution.

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: Systems and methods for correcting intensity drop-offs due to geometric properties of lenses are provided. In one example, a method includes receiving an input pixel of the image data, the image data acquired using an image sensor. A color component of the input pixel is determined. A gain grid is determined by pointing to the gain grid in external memory. Each of the plurality of grid points is associated with a lens shading gain selected based upon the color of the input pixel. A nearest set of grid points that enclose the input pixel is identified. Further, a lens shading gain is determined by interpolating the lens shading gains associated with each of the set of grid points and is applied to the input pixel.

Abstract: Systems and methods for down-scaling are provided. In one example, a method for processing image data includes determining a plurality of output pixel locations using a position value stored by a position register, using the current position value to select a center input pixel from the image data and selecting an index value, selecting a set of input pixels adjacent to the center input pixel, selecting a set of filtering coefficients from a filter coefficient lookup table using the index value, filtering the set of source input pixels to apply a respective one of the set of filtering coefficients to each of the set of source input pixels to determine an output value for the current output pixel at the current position value, and correcting chromatic aberrations in the set of source input pixels.

Abstract: Systems, methods, and devices for sharpening image data are provided. One example of an image signal processing system includes a YCC processing pipeline that includes luma sharpening logic. The luma sharpening logic may sharpen the luma component while avoiding sharpening some noise. Specifically, a multi-scale unsharp mask filter may obtain unsharp signals by filtering an input luma component, and sharp component determination logic may determine sharp signals representing differences between the unsharp signals and the luma component. Sharp lookup tables may “core” the sharp signals, which may prevent some noise from being sharpened. Output logic may determine a sharpened output luma signal by combining the sharp signals with, for example, luma component or one of the unsharp signals.

Abstract: Systems and methods for generating local image statistics are provided. In one example, an image signal processing system may include a statistics pipeline with image processing logic and local image statistics collection logic. The image processing logic may receive and process pixels of raw image data. The local image statistics collection logic may generate a local histogram associated with a luminance of the pixels of a first block of pixels of the raw image data or a thumbnail in which a pixel of the thumbnail represents a downscaled version of the luminance of the pixels of the first block of the pixel. The raw image data may include many other blocks of pixels of the same size as the first block of pixels.

Abstract: Systems and methods for processing raw image data are provided. One example of such a system may include memory to store image data in raw format from a digital imaging device and an image signal processor to process the image data. The image signal processor may include data conversion logic and a raw image processing pipeline. The data conversion logic may convert the image data into a signed format to preserve negative noise from the digital imaging device. The raw image processing pipeline may at least partly process the image data in the signed format. The raw image processing pipeline may also include, among other things, black level compensation logic, fixed pattern noise reduction logic, temporal filtering logic, defective pixel correction logic, spatial noise filtering logic, lens shading correction logic, and highlight recovery logic.

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: The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may collect statistics associated with fixed pattern noise of image data by receiving a first frame of the image data comprising a plurality of pixels. The image processing pipeline may then determine a sum of a first plurality of pixel values that correspond to at least a first portion of the plurality of pixels such that each pixel in at least the first portion of the plurality of pixels is disposed along a first axis within the frame of the image data. After determining the sum of the first plurality of pixel values, the image processing pipeline may store the sum of the first plurality of pixel values in a memory such that the sum of the first plurality of pixel values represent the statistics.

Abstract: Systems and methods for local tone mapping are provided. In one example, an electronic device includes an electronic display, an imaging device, and an image signal processor. The electronic display may display images of a first bit depth, and the imaging device may include an image sensor that obtains image data of a higher bit depth than the first bit depth. The image signal processor may process the image data, and may include local tone mapping logic that may apply a spatially varying local tone curve to a pixel of the image data to preserve local contrast when displayed on the display. The local tone mapping logic may smooth the local tone curve applied to the intensity difference between the pixel and another nearby pixel exceeds a threshold.

Abstract: Temporally filtering raw image data may include a temporal filter that determines a spatial location of a current pixel and identifies at least one collocated reference pixel from a previous frame. A motion delta value is determined based upon the current pixel and its collocated reference pixel. An index is determined based upon the motion delta value and a motion history value corresponding to the current pixel from the previous frame. Using the index, a first filtering coefficient may be selected from a motion table. Then an attenuation factor may be selected from a luma table based upon the value of the current pixel, and a second filtering coefficient may be determined based upon the selected attenuation factor and the first filtering coefficient. The temporally filtered output value corresponding to the current pixel may then be based upon the second filtering coefficient, the current pixel, and the collocated reference pixel.

Abstract: Certain aspects of this disclosure relate to an image signal processing system that includes a flash controller that is configured to activate a flash device prior to the start of a target image frame by using a sensor timing signal. In one embodiment, the flash controller receives a delayed sensor timing signal and determines a flash activation start time by using the delayed sensor timing signal to identify a time corresponding to the end of the previous frame, increasing that time by a vertical blanking time, and then subtracting a first offset to compensate for delay between the sensor timing signal and the delayed sensor timing signal. Then, the flash controller subtracts a second offset to determine the flash activation time, thus ensuring that the flash is activated prior to receiving the first pixel of the target frame.

Abstract: Various techniques are disclosed for processing statistics data in an image signal processor (ISP). In one embodiment, a statistics collection engine may be implemented in a front-end processing unit of the ISP, such that statistics are collected prior to processing by an ISP pipeline downstream from the front-end processing unit. In one embodiment, the statistics collection engine may be configured to acquire statistics relating to auto white-balance, auto-exposure, and auto-focus, as well as flicker detection. Collected statistics may be output to a memory and used by the ISP to process acquired image data.

Abstract: Various techniques for applying binning compensation filtering to binned raw image data acquired by an image sensor are provided. In one embodiment, a binning compensation filter (BCF) includes separate digital differential analyzers (DDA) for vertical and horizontal scaling. A current position of an output pixel is determined by incrementing the DDA based upon a step size. Using the known output pixel position, a center source input pixel and an index corresponding to the between-pixel fractional position of the output pixel position relative to the input pixels may be selected for filtering. Using the selected center input pixel, one or more same-colored neighboring source pixels may be selected. The number of selected source pixels may depend on the number of taps used by the scaling logic, and may depend on whether horizontal or vertical scaling is being applied.

Abstract: Certain embodiments of the present disclosure provide a flexible memory input/output controller that is configured to the storing and reading of multiple types of pixels and pixel memory formats. For instance, the memory I/O controller may support the storing and reading of raw image pixels at various bits of precision, such as 8-bit, 10-bit, 12-bit, 14-bit, and 16-bit. Pixel formats that are unaligned with memory bytes (e.g., not being a multiple of 8-bits) may be stored in a packed manner. The memory I/O controller may also support various formats of RGB pixel sets and YCC pixel sets.

Abstract: The present disclosure provides techniques relates to the implementation of a raw pixel processing unit using a set of line buffers. In one embodiment, the set of line buffers may include a first subset and second subset. Various logical units of the raw pixel processing unit may be implemented using the first and second subsets of line buffers in a shared manner. For instance, in one embodiment, defective pixel correction and detection logic may be implemented using the first subset of line buffers. The second subset of line buffers may be used to implement lens shading correction logic, gain, offset, and clamping logic, and demosaicing logic. Further, noise reduction may also be implemented using at least a portion of each of the first and second subsets of line buffers.