# US 11,909,810 B2 · Image data segmentation and transmission > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,909,810 B2 - Document ID: US11909810B2 - Status: Granted - Kind: B2 - Application number: 17/661,970 - Filed: 2022-05-04 - Published: 2022-08-18 - Granted: 2024-02-20 - Earliest claimed: 2019-11-01 - Assignees: Microsoft Technology Licensing, LLC - Applicants: Microsoft Technology Licensing, LLC - Inventors: Anirudh Badam; Ranveer Chandra; Youjie Li; Sagar Ramanand Jha - Web page: https://patentgrep.com/patent/US11909810B2 ## CPC - H04L 67/06: specially adapted for file transfer, e.g. file transfer protocol [FTP] - G06T 7/00: Image analysis - G06T 7/10: Segmentation; Edge detection (motion-based segmentation G06T7/215) - G06T 7/11: Region-based segmentation - G06T 7/30: Determination of transform parameters for the alignment of images, i.e. image registration - G06T 7/40: Analysis of texture (depth or shape recovery from texture G06T7/529) - G06T 9/00: Image coding (bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00) - G06V 20/13: Satellite images - H04L 67/5651: Reducing the amount or size of exchanged application data - G06T 2207/10016: Video; Image sequence - G06T 2207/10024: Color image - G06T 2207/10028: Range image; Depth image; 3D point clouds - G06T 2207/10032: Satellite or aerial image; Remote sensing - G06T 2207/20048: Transform domain processing - G06T 2207/30252: Vehicle exterior; Vicinity of vehicle - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) The method of claim 1, wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality. ### Claim 3 (depends on 1) 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. ### Claim 4 (depends on 1) 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. ### Claim 5 (depends on 4) The method of claim 4, wherein the compression format is one of JPEG XR, JPEG 2000, and AV1. ### Claim 6 (depends on 1) 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. ### Claim 7 (depends on 1) 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. ### Claim 8 (depends on 1) 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. ### Claim 9 (depends on 1) 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. ### Claim 10 (depends on 9) The method of claim 9, wherein the subset of the one or more source images are images of a target object for analysis. ### Claim 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. ### Claim 12 (depends on 11) The computing device of claim 11, wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality. ### Claim 13 (depends on 11) 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. ### Claim 14 (depends on 11) 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. ### Claim 15 (depends on 11) 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. ### Claim 16 (depends on 11) 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. ### Claim 17 (depends on 11) 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. ### Claim 18 (depends on 11) 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. ### Claim 19 (depends on 18) The computing device of claim 18, wherein the subset of the one or more source images are images of a target object for analysis. ### Claim 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.