Patents by Inventor Alex HAY
Alex HAY has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240265499Abstract: Existing digital image color style transfer encoding methods are often forced to compromise between performing artifact-free local image processing and performing sufficiently expressive global image processing. Moreover, such existing image style encoding methods may be under-constrained (thereby producing more visible artifacts in stylized output images than would be desired) or over-constrained (and thereby not being expressive enough to sufficiently learn and reproduce local/spatial color changes in the stylized output images). Thus, disclosed herein are techniques to combine the advantageous aspects of existing image stylization methods in a novel hybrid image processing method that effectively bifurcates the learning and reproduction of pixel luminance changes from the learning and reproduction of pixel color changes in stylized output images.Type: ApplicationFiled: February 6, 2023Publication date: August 8, 2024Inventors: Han Gong, Alex Hayes
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Patent number: 11622085Abstract: 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.Type: GrantFiled: March 20, 2020Date of Patent: April 4, 2023Assignee: Apple Inc.Inventors: Graham Finlayson, Alex Hayes
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Patent number: 11504456Abstract: A percutaneous drainage device for draining a fluid collection located under the skin of a patient is disclosed. The percutaneous drainage device includes a penetration component slidably engaged with a cannula. The penetration component has a piercing end adapted to penetrate tissue of a patient and introduce an open end of the cannula to a subcutaneous fluid collection site. The cannula may be held in place in the patient by an anchoring means. The cannula provides a passage through which a fluid collection may be drained from a patient. The cannula may be in fluid communication with a collection vessel, which collects fluid collection transported away from the subcutaneous fluid collection site.Type: GrantFiled: November 28, 2017Date of Patent: November 22, 2022Assignee: INOVA MEDICAL PTY LTDInventors: Narciso Vila Ramirez, Ming Khoon Yew, Melanie White, Natasha Ahuja, Alex Hayes
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Patent number: 11471572Abstract: A percutaneous drainage device for draining a fluid collection located under the skin of a patient is disclosed. The percutaneous drainage device includes a penetration component slidably engaged with a cannula. The penetration component has a piercing end adapted to penetrate tissue of a patient and introduce an open end of the cannula to a subcutaneous fluid collection site. The cannula may be held in place in the patient by an anchoring means. The cannula provides a passage through which a fluid collection may be drained from a patient. The cannula may be in fluid communication with a collection vessel, which collects fluid collection transported away from the subcutaneous fluid collection site.Type: GrantFiled: November 28, 2017Date of Patent: October 18, 2022Assignee: INOVA MEDICAL PTY LTDInventors: Narciso Vila Ramirez, Ming Khoon Yew, Melanie White, Natasha Ahuja, Alex Hayes
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Patent number: 11388355Abstract: Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved multi-spectral image processing techniques for generating an enhanced output image, the techniques comprising: obtaining an N-channel (e.g., multispectral) input image; determining fusion weights and fallback weights (e.g., relative intensity weights) for each of the N-channels of the input image; blending the fusion and fallback weights based on an amount of gradient information to generate blended weights; modulating the blended weights for a plurality of frequency band representations of the input image; applying the modulated blended weights to the corresponding frequency band representations of the input image to generate a plurality of output image frequency band representations; producing an output luma image, based on the plurality of output image frequency band representations; and generating an output RGB image, based on the output luma image, which may then, e.g.Type: GrantFiled: June 12, 2020Date of Patent: July 12, 2022Assignee: Apple Inc.Inventors: Alex Hayes, Ilya Romanenko
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Patent number: 11265490Abstract: Devices, methods, and non-transitory program storage devices for spatiotemporal image noise reduction are disclosed, comprising: maintaining an accumulated image in memory; and obtaining a first plurality of multispectral images (e.g., RGB-IR images). For each image in the first plurality of multispectral images, the method may: calculate a multispectral guide image for the current image; calculate blending weights for the current image; apply the calculated blending weights to each channel of the current image to generate a denoised current image; and update the accumulated image based on pixel differences between the denoised current image and the accumulated image. In some embodiments, additional images (e.g., the accumulated image and/or other images captured prior to or after a given current image) may also be included in the denoising operations for a given current image. Finally, the method may generate a denoised output image for each input image, based on the updated accumulated image.Type: GrantFiled: June 15, 2020Date of Patent: March 1, 2022Assignee: Apple Inc.Inventors: Ilya Romanenko, Alex Hayes
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Publication number: 20210374925Abstract: An image enhancement method and system is described. The method comprises receiving an input and target image pair, each of the input and target images including data representing pixel intensities; processing the data to determine a plurality of basis functions, each basis function being determined in dependence on content of the input image, determining a combination of the basis functions to modify the intensity of pixels of the input image to approximate the target image; and applying the plurality of basis functions to the input image to produce an approximation of the target image.Type: ApplicationFiled: May 14, 2021Publication date: December 2, 2021Inventors: Graham Finlayson, Alex Hayes
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Publication number: 20200396398Abstract: Devices, methods, and non-transitory program storage devices for spatiotemporal image noise reduction are disclosed, comprising: maintaining an accumulated image in memory; and obtaining a first plurality of multispectral images (e.g., RGB-IR images). For each image in the first plurality of multispectral images, the method may: calculate a multispectral guide image for the current image; calculate blending weights for the current image; apply the calculated blending weights to each channel of the current image to generate a denoised current image; and update the accumulated image based on pixel differences between the denoised current image and the accumulated image. In some embodiments, additional images (e.g., the accumulated image and/or other images captured prior to or after a given current image) may also be included in the denoising operations for a given current image. Finally, the method may generate a denoised output image for each input image, based on the updated accumulated image.Type: ApplicationFiled: June 15, 2020Publication date: December 17, 2020Inventors: Ilya Romanenko, Alex Hayes
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Publication number: 20200396397Abstract: Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved multi-spectral image processing techniques for generating an enhanced output image, the techniques comprising: obtaining an N-channel (e.g., multispectral) input image; determining fusion weights and fallback weights (e.g., relative intensity weights) for each of the N-channels of the input image; blending the fusion and fallback weights based on an amount of gradient information to generate blended weights; modulating the blended weights for a plurality of frequency band representations of the input image; applying the modulated blended weights to the corresponding frequency band representations of the input image to generate a plurality of output image frequency band representations; producing an output luma image, based on the plurality of output image frequency band representations; and generating an output RGB image, based on the output luma image, which may then, e.g.Type: ApplicationFiled: June 12, 2020Publication date: December 17, 2020Inventors: Alex Hayes, Ilya Romanenko
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Patent number: 10789692Abstract: 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.Type: GrantFiled: November 28, 2016Date of Patent: September 29, 2020Assignee: Apple Inc.Inventors: Graham Finlayson, Alex Hayes
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Publication number: 20200304732Abstract: 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.Type: ApplicationFiled: March 20, 2020Publication date: September 24, 2020Inventors: Graham Finlayson, Alex Hayes
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Publication number: 20140374577Abstract: An optical power meter including a mechanical interface that establishes a predetermined air gap, while avoiding physical contact with the sensitive area of the DUT. The mechanical interface is formed such that the test instrument contacts the DUT in the non-sensitive region over an area large enough to establish contact pressure that is well within the strength of the DUT's material. Accordingly, the non-contacting optical element enables optical power to be collected and relayed with a quantifiable and repeatable power loss. A high-NA, large area optical element is used to collect and relay optical power accurately while maintaining low sensitivity to axial or radial alignment.Type: ApplicationFiled: June 24, 2014Publication date: December 25, 2014Inventors: Kevin G. CASSADY, Eric THOMPSON,, Matthew BROWN, Craig BLACK, Scott DEVORE, Samuel S. FRANK, Alex HAY