摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.