Apple Inc.

University of East Anglia

Uea Enterprises Limited

Spectral Edge Limited

Other

Hewlett-packard Development Company, L.P.

Graham D Finlayson

Mark Drew

Steven David Hordley

Clement Fredembach

Guy Cote

Suk Hwan Lim

D Amnon Silverstein

Joseph P Bratt

Weichun Ku

Jakkarin Singnoo

Paul M Hubel

Alex Hayes

David Connah

Xuemei Zhang

Nicolas P Bonnier

Noah Denis Bedard

Ilya Romanenko

Bosheng Zhang

Claus Moelgaard

Roberto Montagna

Jason P De Villiers

Ruixia Xu

Elisabetta Trezzi

Cheng Lu

Stephen Hordley

Steven D Hordley

Alexandra S Ludlow

Tobias Baldauf

Hau Ling Hung

Yuteng Zhu

A system and method for generating a colour filter for modifying the spectral response of a vision system are disclosed. The method includes receiving an RGB spectral response of the vision system for a colour target under predetermined illumination and executing, by a processor of a computer system, computer program instructions configured to apply the RGB spectral response to a bilinear optimisation problem that simultaneously determines: i) a colour correction matrix to transform the RGB spectral response to XYZ colour space; and, ii) parameters of the colour filter. The method further executes computer program instructions configured solving the bilinear optimisation problem; and then provides the parameters or causes a colour filter to be formed using the parameters.

System and method for generating a colour filter for modifying the spectral response of a vision system

Embodiments disclosed herein are directed to devices and methods for performing spatially-varying brightness correction of a flash image. The spatially-varying brightness correction utilizes a set of images that includes one or more images captured under flash illumination and one or more images captured without flash illumination, which are used to decompose one of the flash images or an image generated therefrom into a flash contribution image and an ambient contribution image. The flash contribution image and the ambient contribution image are recombined to generate a corrected flash image, and information about the flash module and/or scene is used to adjust the relative contributions of these images during recombination.

Techniques for correcting images in flash photography

A method of creating a multispectral decorrelation model for use in determining a visible image from a multispectral image captured using a multispectral image sensor, the method comprising the steps of: generating, using a plurality of quantum efficiency curves for the multispectral image sensor and a plurality of synthetic light spectrum vectors, a grid of synthetic multispectral pixel values and a corresponding grid of synthetic visible pixel values, wherein each synthetic visible pixel value is substantially decorrelated from a non-visible component of a corresponding synthetic multispectral pixel value; and determining a multispectral decorrelation model using the grid of synthetic multispectral pixel values and the corresponding grid of synthetic visible pixel values, wherein the multispectral decorrelation model in use maps a multispectral pixel value of the multispectral image to a visible pixel value of the visible image.

Multispectral image decorrelation method and system

Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved image processing, the techniques comprising: obtaining an input image and target image data, and then calculating derivatives for the target image data using a regularized derivative kernel operator. In some embodiments, the regularized operator may comprise the following operator: [&#x2212;1 (1+&#x3b5;)], wherein &#x3b5; may be a controllable system parameter and preferably is independent of the particular type of image processing being applied to the image. In some embodiments, the techniques may find look-up table (LUT) mappings or analytical functions to approximate the derivative structure of the target image data. Finally, the techniques disclosed herein may generate an output image from the input image based on attempting to closely approximate the calculated derivatives for the target image data. In preferred embodiments, by controlling the mapping, e.g., using regularization techniques, halos and other image artifacts may be ameliorated.

Regularized derivative operators for image processing system and method

A method and system for generating an output image from a plurality, N, of corresponding input image channels is described. A Jacobian matrix of the plurality of corresponding input image channels is determined. The principal characteristic vector of the outer product of the Jacobian matrix is calculated. The sign associated with the principal characteristic vector is set whereby an input image channel pixel projected by the principal characteristic vector results in a positive scalar value. The output image as a per-pixel projection of the input channels in the direction of the principal characteristic vector is generated.

Method and system for generating an output image from a plurality of corresponding input image channels

A method and system for determining parameters of an image processing pipeline of a digital camera is disclosed. The image processing pipeline transforms captured image data on a scene into rendered image data. Rendered image data produced by the image processing pipeline of the camera is obtained from the captured image data on the scene. At least a subset of the captured image data on the scene is determined and a ranking order for pixels of the rendered image data is obtained. A set of constraints from the captured image data and the ranked rendered image data is determined, each constraint of the set being determined in dependence on selected pair combinations of pixel values when taken in said ranking order of the rendered image data and corresponding pair combinations of the captured image data. Parameters of the image processing pipeline are determined that satisfy the sets of constraints.

Method and system for determining parameters of an image processing pipeline of a digital camera

An image processing method, system and device are disclosed. In the method, sensor responses for an input image are estimated, the sensor responses including sensor responses for cone sensors including a first cone sensor set and a second, different, cone sensor set. In dependence on the sensor responses, a transform mapping for application to a source image is determined to generate a modified image.

Image processing method and system

Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Global approximation to spatially varying tone mapping operators

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.

Systems and methods for local tone mapping

A method and system for producing a scalar image from a derivative field and a vector image is disclosed. A function class c is selected, where all members of the class c are functions which map each vector of the vector image to a unique scalar value. A function f is selected from the class c which maps the vector image to a scalar image, the derivative of which is closest to the derivative field. The scalar image is generated from the vector image by using f to calculate each scalar value in the scalar image from a corresponding vector in the vector image.

Image reconstruction method and system

A method of generating an image enhancement function for enhancing an input image comprising a plurality of pixels to form an enhanced output image. The method includes receiving a reference image comprising a plurality of pixels; receiving an enhanced image derived from the reference image comprising a corresponding plurality of pixels; calculating a plurality of lookup tables, each of which maps a first plurality of pixel values to a second plurality of pixel values; and generating the image enhancement function comprising a spatially varying function of the lookup tables which when applied to the reference image generates an approximation to the enhanced image.

Method and system for generating enhanced images

Methods to generate, and devices to use, an adaptive tone curve generation operation are disclosed. Tone curves so generated have been found to produce stable tone mapping in a wide range of operational environments, including during multi-exposure fused images (e.g., during high dynamic range image fusion). In general, techniques are disclosed that use a content-load histogram in combination with image capture device noise information to adaptively bound a tone curve's slope and, therefore, the resulting tone curve. As used here, a content-load histogram is a histogram that captures spatial, color or other information carried by an image's pixels at various gray levels.

Noise-constrained tone curve generation

Growing community of inventors

Taverham, United Kingdom

Graham D Finlayson