# US 10,311,557 B2 · Automated tonal balancing

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- Number: US 10,311,557 B2
- Document ID: US10311557B2
- Status: Granted
- Kind: B2
- Application number: 15/445,949
- Filed: 2017-02-28
- Published: 2017-10-19
- Granted: 2019-06-04
- Earliest claimed: 2014-05-08
- Assignees: DigitalGlobe, Inc.
- Applicants: DigitalGlobe, Inc.
- Inventors: Nathan Reid Swanson; Patrick Young; Spencer Stirling
- Web page: https://patentgrep.com/patent/US10311557B2

## CPC

- G06T 5/92: based on global image properties
- G06T 3/4038: Image mosaicing, e.g. composing plane images from plane sub-images
- G06T 5/70: Denoising; Smoothing
- G06T 5/73: Deblurring; Sharpening
- G06T 5/94: based on local image properties, e.g. for local contrast enhancement
- G06T 2200/32: involving image mosaicing
- G06T 2207/10024: Color image
- G06T 2207/10032: Satellite or aerial image; Remote sensing
- G06T 2207/20008: Globally adaptive
- G06T 2207/20012: Locally adaptive
- G06T 2207/20208: High dynamic range [HDR] image processing
- G06T 2207/30181: Earth observation
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A system for automated tonal balancing, comprising a rectification server that groups and processes images for use in tone-matching and provides them to a tone-matching server, that then performs tone-matching operations on the images and provides them as output for review or storage, and methods for tonal balancing using the system of the invention.

## Claims

### Claim 1

A system for automated generation of large-scale tonally-balanced orthomosaic images, comprising:
a tone-balancing server computer comprising a memory, a processor, and a plurality of programming instructions stored in the memory, wherein the programming instructions, when loaded into the processor, cause the processor to:
receive a group of orthorectified input images associated with a geographic region;
obtain a reference image for the geographic region;
for each orthorectified input image:
subdivide the respective orthorectified input image into a plurality of patches;
compute a pixel-level tonal mapping function for each patch to match a corresponding set of pixels of the reference image;
compute a first global tonal mapping function for the respective orthorectified input image by, for each pair of patches of the respective orthorectified input image, computing a function that smoothly connects the respective pixel-level tonal mapping functions for the pair of patches; and
apply the first global tonal mapping function to each pixel of the respective orthorectified input image to create a respective tonally-balanced orthorectified output image;
compute a second global tonal mapping reference by smoothly matching first global tonal matching functions for each neighboring pair of orthorectified output images; and
apply the second global tonal matching function to each pixel of each tonally-balanced orthorectified output image.

### Claim 2

A method for automatically generating large-scale tonally-balanced orthomosaic images, the method comprising the steps of:
receiving, at a tone-balancing server computer comprising program code stored in a memory, a group of orthorectified input images associated with a geographic region;
obtaining a reference image for the geographic region;
for each orthorectified input image, performing the steps of:
subdividing the orthorectified input image into a plurality of patches;
computing a pixel-level tonal mapping function for each patch to match a corresponding set of pixels of the reference image;
computing a first global tonal mapping function for the respective orthorectified input image by, for each pair of patches of the respective orthorectified input image, computing a function that smoothly connects the respective pixel-level tonal mapping functions for the pair of patches; and
applying the first global tonal mapping function to each pixel of the respective orthorectified input image to create a plurality of tonally-balanced orthorectified output images;
computing a second global tonal mapping reference by smoothly matching first global tonal matching functions for each neighboring pair of orthorectified output images; and
applying the second global tonal matching function to each pixel of each tonally-balanced orthorectified output image.