Gopro, Inc.

Michael Serge Andre Kraak

Thomas Nicolas Emmanuel Veit

Guillaume Matthieu Guérin

Bruno César Douady

Thomas Derbanne

Bruno César Douady-Pleven

Bruno Cesar Douady-Pleven

Guillaume Matthieu Guèrin

Systems and methods are disclosed for image signal processing. For example, methods may include receiving a current image of a sequence of images from an image sensor; combining the current image with a recirculated image to obtain a noise reduced image, where the recirculated image is based on one or more previous images of the sequence of images from the image sensor; determining a noise map for the noise reduced image, where the noise map is determined based on estimates of noise levels for pixels in the current image, a noise map for the recirculated image, and a set of mixing weights; recirculating the noise map with the noise reduced image to combine the noise reduced image with a next image of the sequence of images from the image sensor; and storing, displaying, or transmitting an output image that is based on the noise reduced image.

Three-dimensional noise reduction

A non-transitory computer-readable storage medium stores executable instructions that, when executed by a processor, cause performance of operations comprising operations to access an image captured by an image sensor, obtain a transfer function for mapping pixel values, determine a faces indication that reflects a proportion of a scene depicted in the image that includes one or more human faces, and modify the transfer function based on the faces indication. Modifying the transfer function based on the faces indication comprises adjusting a gain of the transfer function to move the gain closer to unity. The operations include to apply the transfer function to pixel values of the image to produce a tone mapped image and output the tone mapped image.

Global tone mapping

A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.

Systems and methods are disclosed for image signal processing. For example, systems may include an image sensor and a processing apparatus. The image sensor captures image data using a plurality of selectable exposure times. The processing apparatus receives a first image from the image sensor captured with a first exposure time and receives a second image from the image sensor captured with a second exposure time that is less than the first exposure time. A high dynamic range image is determined based on the first image and the second image, wherein an image portion of the high dynamic range image is based on a corresponding image portion of the second image when a pixel of a corresponding image portion of the first image is saturated. An output image that is based on the high dynamic range image is stored, displayed, or transmitted.

System, method, and apparatus for determining a high dynamic range image

Generating a calibrated camera alignment model for image capture devices having overlapping fields-of-view may include identifying a camera alignment model describing a first candidate alignment path for a defined location in a first input frame and a second candidate alignment path for the defined location in a second input frame, identifying a third candidate alignment path spatially adjacent to the first candidate alignment path, identifying a fourth candidate alignment path spatially adjacent to the second candidate alignment path, identifying a first point along the first candidate alignment path or the second candidate alignment path corresponding to a second point along the third candidate alignment path or the fourth candidate alignment path, and updating the camera alignment model based on the first point, the second point, or both.

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Cachan, France

Michael Serge Andre Kraak