Patents by Inventor Hau Hwang
Hau Hwang 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).
-
Publication number: 20240054681Abstract: Techniques are provided for using one or more machine learning systems to process input data including image data. The input data including the image data can be obtained, and at least one machine learning system can be applied to at least a portion of the image data to determine at least one color component value for one or more pixels of at least the portion of the image data. Based on application of the at least one machine learning system to at least the portion of the image data, output image data for a frame of output image data can be generated. The output image data includes at least one color component value for one or more pixels of the frame of output image data. Application of the at least one machine learning system causes the output image data to have a reduced dimensionality relative to the input data.Type: ApplicationFiled: October 25, 2023Publication date: February 15, 2024Inventors: Hau HWANG, Tushar Sinha PANKAJ, Vishal GUPTA, Jinsoo LEE
-
Patent number: 11836951Abstract: Techniques are provided for using one or more machine learning systems to process input data including image data. The input data including the image data can be obtained, and at least one machine learning system can be applied to at least a portion of the image data to determine at least one color component value for one or more pixels of at least the portion of the image data. Based on application of the at least one machine learning system to at least the portion of the image data, output image data for a frame of output image data can be generated. The output image data includes at least one color component value for one or more pixels of the frame of output image data. Application of the at least one machine learning system causes the output image data to have a reduced dimensionality relative to the input data.Type: GrantFiled: February 4, 2022Date of Patent: December 5, 2023Assignee: QUALCOMM IncorporatedInventors: Hau Hwang, Tushar Sinha Pankaj, Vishal Gupta, Jisoo Lee
-
Publication number: 20230388623Abstract: Systems and techniques are described for image processing. An imaging system can include an image sensor that captures image data. An image signal processor (ISP) of the imaging system can demosaic the image data. The imaging system can input the image data into one or more trained machine learning models, in some cases along with metadata associated with the image data. The one or more trained machine learning models can output settings for a set of parameters of the ISP based on the image data and/or the metadata. The imaging system can generate an output image by processing the image data using the ISP, with the parameters of the ISP set according to the settings. Each pixel of the pixels of the image data can be processed using a respective setting for adjusting a corresponding parameter. The parameters of the ISP can include gain, offset, gamma, and Gaussian filtering.Type: ApplicationFiled: August 10, 2023Publication date: November 30, 2023Inventors: Hau HWANG, Shusil DANGI
-
Patent number: 11778305Abstract: Systems and techniques are described for image processing. An imaging system can include an image sensor that captures image data. An image signal processor (ISP) of the imaging system can demosaic the image data. The imaging system can input the image data into one or more trained machine learning models, in some cases along with metadata associated with the image data. The one or more trained machine learning models can output settings for a set of parameters of the ISP based on the image data and/or the metadata. The imaging system can generate an output image by processing the image data using the ISP, with the parameters of the ISP set according to the settings. Each pixel of the pixels of the image data can be processed using a respective setting for adjusting a corresponding parameter. The parameters of the ISP can include gain, offset, gamma, and Gaussian filtering.Type: GrantFiled: June 18, 2021Date of Patent: October 3, 2023Assignee: QUALCOMM IncorporatedInventors: Hau Hwang, Shusil Dangi
-
Publication number: 20220408012Abstract: Systems and techniques are described for image processing. An imaging system can include an image sensor that captures image data. An image signal processor (ISP) of the imaging system can demosaic the image data. The imaging system can input the image data into one or more trained machine learning models, in some cases along with metadata associated with the image data. The one or more trained machine learning models can output settings for a set of parameters of the ISP based on the image data and/or the metadata. The imaging system can generate an output image by processing the image data using the ISP, with the parameters of the ISP set according to the settings. Each pixel of the pixels of the image data can be processed using a respective setting for adjusting a corresponding parameter. The parameters of the ISP can include gain, offset, gamma, and Gaussian filtering.Type: ApplicationFiled: June 18, 2021Publication date: December 22, 2022Inventors: Hau HWANG, Shusil DANGI
-
Publication number: 20220215588Abstract: Techniques are provided for using one or more machine learning systems to process input data including image data. The input data including the image data can be obtained, and at least one machine learning system can be applied to at least a portion of the image data to determine at least one color component value for one or more pixels of at least the portion of the image data. Based on application of the at least one machine learning system to at least the portion of the image data, output image data for a frame of output image data can be generated. The output image data includes at least one color component value for one or more pixels of the frame of output image data. Application of the at least one machine learning system causes the output image data to have a reduced dimensionality relative to the input data.Type: ApplicationFiled: February 4, 2022Publication date: July 7, 2022Inventors: Hau HWANG, Tushar Sinha PANKAJ, Vishal GUPTA, Jisoo LEE
-
Publication number: 20220101133Abstract: A method performed by a deep neural network (DNN) includes receiving, at a layer of the DNN during an inference stage, a layer input comprising content associated with a DNN input received at the DNN. The method also includes quantizing one or more parameters of a plurality of parameters associated with the layer based on the content of the layer input. The method further includes performing a task corresponding to the DNN input, the task performed with the one or more one quantized parameters.Type: ApplicationFiled: September 28, 2021Publication date: March 31, 2022Inventors: Randy ARDYWIBOWO, Venkata Ravi Kiran DAYANA, Hau HWANG
-
Patent number: 11263782Abstract: Techniques are provided for using one or more machine learning systems to process input data including image data. The input data including the image data can be obtained, and at least one machine learning system can be applied to at least a portion of the image data to determine at least one color component value for one or more pixels of at least the portion of the image data. Based on application of the at least one machine learning system to at least the portion of the image data, output image data for a frame of output image data can be generated. The output image data includes at least one color component value for one or more pixels of the frame of output image data. Application of the at least one machine learning system causes the output image data to have a reduced dimensionality relative to the input data.Type: GrantFiled: March 10, 2020Date of Patent: March 1, 2022Assignee: QUALCOMM IncorporatedInventors: Hau Hwang, Tushar Sinha Pankaj, Vishal Gupta, Jisoo Lee
-
Publication number: 20210360179Abstract: An imaging system can obtain image data, for instance from an image sensor. The imaging system can supply the image data as input data to a machine learning system, which can generate one or more maps based on the image data. Each map can identify strengths at which a certain image processing function is to be applied to each pixel of the image data. Different maps can be generated for different image processing functions, such as noise reduction, sharpening, or color saturation. The imaging system can generate a modified image based on the image data and the one or more maps, for instance by applying each of one or more image processing functions in accordance with each of the one or more maps. The imaging system can supply the image data and the one or more maps to a second machine learning system to generate the modified image.Type: ApplicationFiled: May 10, 2021Publication date: November 18, 2021Inventors: Shusil DANGI, Hau HWANG, Venkata Ravi Kiran DAYANA
-
Patent number: 10904637Abstract: Techniques and systems are provided for providing a rendering engine model for raw media data. In some examples, a system obtains media data captured by a data capturing device and embeds, in a media item containing the media data, a rendering engine model including a description of a neural network configured to process the media data and generate a particular media data output, the description defining a neural network architecture for the neural network. The system then outputs the media item with the rendering engine model embedded in the media item, the rendering engine model indicating how to execute the neural network to process the media data in the media item and generate the particular media data output based on the description of the neural network.Type: GrantFiled: December 17, 2018Date of Patent: January 26, 2021Assignee: Qualcomm IncorporatedInventors: Hau Hwang, Jisoo Lee, Jiafu Luo
-
Publication number: 20200211229Abstract: Techniques are provided for using one or more machine learning systems to process input data including image data. The input data including the image data can be obtained, and at least one machine learning system can be applied to at least a portion of the image data to determine at least one color component value for one or more pixels of at least the portion of the image data. Based on application of the at least one machine learning system to at least the portion of the image data, output image data for a frame of output image data can be generated. The output image data includes at least one color component value for one or more pixels of the frame of output image data. Application of the at least one machine learning system causes the output image data to have a reduced dimensionality relative to the input data.Type: ApplicationFiled: March 10, 2020Publication date: July 2, 2020Inventors: Hau HWANG, Tushar Sinha PANKAJ, Vishal GUPTA, Jisoo LEE
-
Publication number: 20200196024Abstract: Techniques and systems are provided for providing a rendering engine model for raw media data. In some examples, a system obtains media data captured by a data capturing device and embeds, in a media item containing the media data, a rendering engine model including a description of a neural network configured to process the media data and generate a particular media data output, the description defining a neural network architecture for the neural network. The system then outputs the media item with the rendering engine model embedded in the media item, the rendering engine model indicating how to execute the neural network to process the media data in the media item and generate the particular media data output based on the description of the neural network.Type: ApplicationFiled: December 17, 2018Publication date: June 18, 2020Inventors: Hau HWANG, Jisoo Lee, Jiafu LUO
-
Patent number: 10643306Abstract: Techniques and systems are provided for processing image data using one or more neural networks. For example, a patch of raw image data can be obtained. The patch can include a subset of pixels of a frame of raw image data, and the frame can be captured using one or more image sensors. The patch of raw image data includes a single color component for each pixel of the subset of pixels. At least one neural network can be applied to the patch of raw image data to determine a plurality of color component values for one or more pixels of the subset of pixels. A patch of output image data can then be generated based on application of the at least one neural network to the patch of raw image data. The patch of output image data includes a subset of pixels of a frame of output image data, and also includes the plurality of color component values for one or more pixels of the subset of pixels of the frame of output image data.Type: GrantFiled: May 30, 2018Date of Patent: May 5, 2020Assignee: QUALCOMM IncoporatedInventors: Hau Hwang, Tushar Sinha Pankaj, Vishal Gupta, Jisoo Lee
-
Publication number: 20190108618Abstract: Techniques and systems are provided for processing image data using one or more neural networks. For example, a patch of raw image data can be obtained. The patch can include a subset of pixels of a frame of raw image data, and the frame can be captured using one or more image sensors. The patch of raw image data includes a single color component for each pixel of the subset of pixels. At least one neural network can be applied to the patch of raw image data to determine a plurality of color component values for one or more pixels of the subset of pixels. A patch of output image data can then be generated based on application of the at least one neural network to the patch of raw image data. The patch of output image data includes a subset of pixels of a frame of output image data, and also includes the plurality of color component values for one or more pixels of the subset of pixels of the frame of output image data.Type: ApplicationFiled: May 30, 2018Publication date: April 11, 2019Inventors: Hau HWANG, Tushar Sinha PANKAJ, Vishal GUPTA, Jisoo LEE
-
Patent number: 10171791Abstract: Apparatus and methods for conditional display of a stereoscopic image pair on a display device are disclosed. In some aspects, a vertical disparity between two images is corrected. If the corrected vertical disparity is below a threshold, a three dimensional image may be generated based on the correction. In some cases, the corrected vertical disparity may still be significant, for example, above the threshold. In these instances, the disclosed apparatus and methods may display a two dimensional image.Type: GrantFiled: June 22, 2016Date of Patent: January 1, 2019Assignee: QUALCOMM IncorporatedInventors: Hau Hwang, Szepo Robert Hung, Ruben Manuel Velarde
-
Publication number: 20160301913Abstract: Apparatus and methods for conditional display of a stereoscopic image pair on a display device are disclosed. In some aspects, a vertical disparity between two images is corrected. If the corrected vertical disparity is below a threshold, a three dimensional image may be generated based on the correction. In some cases, the corrected vertical disparity may still be significant, for example, above the threshold. In these instances, the disclosed apparatus and methods may display a two dimensional image.Type: ApplicationFiled: June 22, 2016Publication date: October 13, 2016Inventors: Hau Hwang, Szepo Robert Hung, Ruben M. Valarde
-
Patent number: 9402065Abstract: Apparatus and methods for conditional display of a stereoscopic image pair on a display device are disclosed. Particularly, some implementations include receiving a first image and a second image, determining a vertical disparity between the first image and the second images, and displaying a stereoscopic image pair if the vertical disparity is below a threshold. Some implementations provide for correcting the vertical disparity by generating at least one corrected image, and generating the stereoscopic image pair based on the corrected image. Some implementations may evaluate the quality of the stereoscopic image pair, and display either a two dimensional image or the stereoscopic image pair based on the evaluation.Type: GrantFiled: September 29, 2011Date of Patent: July 26, 2016Assignee: QUALCOMM IncorporatedInventors: Hau Hwang, Szepo Robert Hung, Ruben M. Velarde
-
Patent number: 9351013Abstract: Methods and apparatus are presented herein to perform selective and/or scalable complexity control of the video codec, so that the amount of processing resources consumed by a video codec may be increased or reduced. Based on the configurable thresholds set within complexity control algorithms, the nonpredictive and the predictive coding sections of the video codec may be selectively implemented. The configurable thresholds are used to determine whether a desired amount of spatial information, such as texture information or motion information, is present within a video frame.Type: GrantFiled: November 13, 2003Date of Patent: May 24, 2016Assignee: QUALCOMM INCORPORATEDInventors: Khaled El-Maleh, Hau Hwang
-
Patent number: 9001227Abstract: A method of combining data from multiple sensors is disclosed. The method includes providing a common control signal to multiple image sensors. Each of the multiple image sensors is responsive to the common control signal to generate image data. The method also includes receiving synchronized data output from each of the multiple image sensors.Type: GrantFiled: April 4, 2011Date of Patent: April 7, 2015Assignee: QUALCOMM IncorporatedInventors: Milivoje Aleksic, Sergiu R. Goma, Hau Hwang, Joseph Cheung
-
Patent number: 8994843Abstract: This disclosure describes techniques for producing high dynamic range images by applying a variable weighting factor to a sample prior to combining the sample with another sample. In one example, a method includes sampling a first pixel cell signal at a first time to produce a first sample, sampling a second pixel cell signal at a second time to produce a second sample, applying a variable weighting factor to the second sample, wherein the variable weighting factor is defined based on a function, and combining the first sample and the weighted second sample.Type: GrantFiled: September 1, 2010Date of Patent: March 31, 2015Assignee: QUALCOMM IncorporatedInventors: Kalin M. Atanassov, Ruben M. Velarde, Hau Hwang