Method and device for de-noising images
US-2019355099-A1 · Nov 21, 2019 · US
US2022263921A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2022263921-A1 |
| Application number | US-202217661970-A |
| Country | US |
| Kind code | A1 |
| Filing date | May 4, 2022 |
| Priority date | Nov 1, 2019 |
| Publication date | Aug 18, 2022 |
| Grant date | — |
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A computing device is provided, including a logic subsystem with one or more processors, and memory storing instructions executable by the logic subsystem. These instructions are executed to obtain one or more source images, segment the one or more source images to generate a plurality of segments, determine a priority order for the plurality of segments, and transmit the plurality of segments to a remote computing device in the priority order. The plurality of segments are spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images. A remote computing device may receive these components in priority order, and perform certain algorithms on individual components without waiting for the entire image to upload.
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1 . A method comprising: performing spatial decomposition and/or frequency decomposition of one or more source images to thereby respectively generate a plurality of spatial components and/or frequency components; determining a priority order for the plurality of spatial components and/or frequency components, wherein the priority order is determined by: adding noise to or performing quality degradation on one or more of the plurality of spatial components and/or frequency components, obtaining a measurement of an effect of the noise or the quality degradation on objects in the one or more source images, and determining the priority order based at least in part on the measurement; and transmitting the plurality of spatial components and/or frequency components to a remote computing device in the priority order. 2 . The method of claim 1 , wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality. 3 . The method of claim 1 , wherein the components comprise the frequency components; and the frequency decomposition is a decomposition of a frequency of visual characteristics of the one or more source images. 4 . The method of claim 1 , wherein the components comprise the frequency components; and the one or more source images are encoded in a compression format that supports the frequency decomposition. 5 . The method of claim 4 , wherein the compression format is one of JPEG XR, JPEG 2000, and AV1. 6 . The method of claim 1 , wherein the components comprise the spatial components; and the spatial components are generated via at least one of human input or a machine learning algorithm trained on labeled visual features. 7 . The method of claim 1 , wherein the components comprise the spatial components and the frequency components; and the frequency components are generated first, followed by the spatial components for each of the frequency components. 8 . The method of claim 1 , further comprising: applying an application sensitivity algorithm to add the noise to, or perform the quality degradation on, each component. 9 . The method of claim 1 , wherein the one or more source images are filtered to select a subset of the one or more of source images to perform spatial decomposition and/or frequency decomposition and transmit. 10 . The method of claim 9 , wherein the subset of the one or more source images are images of a target object for analysis. 11 . A computing device, comprising: a logic subsystem comprising one or more processors; and memory storing instructions executable by the logic subsystem to: perform spatial decomposition and/or frequency decomposition of one or more source images to thereby respectively generate a plurality of spatial components and/or frequency components; determine a priority order for the plurality of spatial components and/or frequency components, wherein the priority order is determined by: adding noise to or performing quality degradation on one or more of the plurality of spatial components and/or frequency components, obtaining a measurement of an effect of the noise or the quality degradation on objects in the one or more source images, and determining the priority order based at least in part on the measurement; and transmitting the plurality of spatial components and/or frequency components to a remote computing device in the priority order. 12 . The computing device of claim 11 , wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality. 13 . The computing device of claim 11 , wherein the components comprise the frequency components; and the frequency decomposition is a decomposition of a frequency of visual characteristics of the one or more source images. 14 . The computing device of claim 11 , wherein the components comprise the frequency components; and the one or more source images are encoded in a compression format that supports the frequency decomposition. 15 . The computing device of claim 11 , wherein the components comprise the spatial components; and the spatial components are generated via at least one of human input or a machine learning algorithm trained on labeled visual features. 16 . The computing device of claim 11 , wherein the components comprise the spatial components and the frequency components; and the frequency components are generated first, followed by the spatial components for each of the frequency components. 17 . The computing device of claim 11 , wherein an application sensitivity algorithm is applied to add the noise to or perform the quality degradation on each component. 18 . The computing device of claim 11 , wherein the one or more source images are filtered to select a subset of the one or more source images to segment and transmit. 19 . The computing device of claim 18 , wherein the subset of the one or more source images are images of a target object for analysis. 20 . A computing device, comprising: a logic subsystem comprising one or more processors; and memory storing instructions executable by the logic subsystem to: perform spatial decomposition and/or frequency decomposition of one or more source images to thereby respectively generate a plurality of spatial components and/or frequency components; determine a priority order for the plurality of spatial components and/or frequency components, wherein the priority order is determined by: adding noise to or performing quality degradation on one or more of the plurality of spatial components and/or frequency components, obtaining a measurement of an effect of the noise or the quality degradation on objects in the one or more source images, and determining the priority order based at least in part on the measurement; and transmitting the plurality of spatial components and/or frequency components to a remote computing device in the priority order.
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