Patent application number | Description | Published |
20130321671 | SYSTEMS AND METHOD FOR REDUCING FIXED PATTERN NOISE IN IMAGE DATA - 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. | 12-05-2013 |
20130321672 | SYSTEMS AND METHODS FOR COLLECTING FIXED PATTERN NOISE STATISTICS OF IMAGE DATA - 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. | 12-05-2013 |
20130321673 | Systems and Methods for Determining Noise Statistics of Image Data - The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may compute noise statistics associated with image data by receiving a frame of the image data having a plurality of pixels. The image processing pipeline may then identify a plurality of portions of the frame of the image data such that each portion of the plurality of portions has a flat surface. The image processing pipeline may then calculate a plurality of gradients for each portion of the plurality of portions, determine one or more dominant gradient orientations for each portion of the plurality of portions, and generate a histogram that represents a plurality of dominant gradient orientations that corresponds to the plurality of portions. After generating the histogram, the image processing pipeline may store the histogram, which may represent the noise statistics, in a memory. | 12-05-2013 |
20130321676 | Green Non-Uniformity Correction - 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. | 12-05-2013 |
20130321677 | SYSTEMS AND METHODS FOR RAW IMAGE PROCESSING - 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. | 12-05-2013 |
20130321678 | SYSTEMS AND METHODS FOR LENS SHADING CORRECTION - 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. | 12-05-2013 |
20130321679 | SYSTEMS AND METHODS FOR HIGHLIGHT RECOVERY IN AN IMAGE SIGNAL PROCESSOR - Image sensors have finite ranges of illuminance that may be captured. When the sensors for particular pixels receive an amount of light exceeding these finite ranges, the pixel values clip to the maximum pixel value. Systems and methods for estimating pixel values that are clipped or near clipping are provided. In one example, a method for processing image data includes determining that a first channel of the image data is saturated or near saturation. The method further includes computing a highlight recovery value for the first channel based upon alternative channels in the image data that are not saturated or near saturation. The highlight recovery value is applied to the first channel. | 12-05-2013 |
20130322745 | Local Image Statistics Collection - 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. | 12-05-2013 |
20130322746 | SYSTEMS AND METHODS FOR YCC IMAGE PROCESSING - 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. | 12-05-2013 |
20130322753 | SYSTEMS AND METHODS FOR LOCAL TONE MAPPING - 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. | 12-05-2013 |
20140010480 | SYSTEMS AND METHODS FOR STATISTICS COLLECTION USING CLIPPED PIXEL TRACKING - 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. | 01-09-2014 |
20150071537 | Image Tone Adjustment using Local Tone Curve Computation - 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. | 03-12-2015 |
20150085150 | In-Stream Rolling Shutter Compensation - 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. | 03-26-2015 |