IP Library › Granted Patent US 12,249,054
Granted Patent B2
US 12,249,054 · App. 18/411,985 · Granted Mar 11, 2025

Dynamic tone mapping

Inventors: Sheng Yuan Chiu (San Jose, CA); Kunlung Wu (San Jose, CA)
Assignee: Roku, Inc.
G06T5/92G06T5/40G06T5/50G06T7/0002H04N5/20G06T2200/24G06T2207/10016G06T2207/20208
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Quick Facts
Patent No.
US 12,249,054
App. No.
18/411,985
Granted
Mar 11, 2025
Kind
B2
Abstract

Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for dynamic tone mapping of video content. An example embodiment operates by identifying, by a dynamic tone mapping system executing on a media device, characteristics of a first video signal having a first dynamic range based on a frame-by-frame analysis of the first video signal. The example embodiment further operates by modifying, by the dynamic tone mapping system, a tone mapping curve based on the characteristics of the first video signal to generate a modified tone mapping curve. Subsequently, the example embodiment operates by converting, by the dynamic tone mapping system, the first video signal based on the modified tone mapping curve to generate a second video signal having a second dynamic range that is less than the first dynamic range.

Claims (40)

1. A computer-implemented method for dynamic tone mapping of video content, comprising:

receiving, by at least one computer processor, histogram data associated with a first video signal representing a video program, wherein the first video signal has a first dynamic range and static metadata describing one or more brightness characteristics of the video program, wherein the histogram data comprises color values for a plurality of frames in the first video signal outputted by a display device;

determining a cumulative histogram for a scene in the video program based on the histogram data;

determining a near-brightest pixel for the scene in the video program based on the cumulative histogram, wherein the near-brightest pixel is a representative pixel value that defines a maximum target brightness value for proper display of the scene;

modifying a tone mapping curve based on the near-brightest pixel and characteristics of the display device to generate a modified tone mapping curve; and

converting the first video signal based on the modified tone mapping curve to generate a second video signal having a second dynamic range that is less than the first dynamic range.

2. The computer-implemented method of claim 1 , wherein the modifying the tone mapping curve comprises:

modifying the tone mapping curve based on a user setting.

3. The computer-implemented method of claim 2 , further comprising:

adapting the second video signal to the user setting.

4. The computer-implemented method of claim 1 , wherein the modifying the tone mapping curve comprises:

temporally filtering the modified tone mapping curve.

5. The computer-implemented method of claim 1 , wherein the determining the near-brightest pixel for the scene in the video program comprises:

determining the near-brightest pixel for the scene in the video program by identifying, using the cumulative histogram, a pixel value in the scene that belongs to a top percentage value of brightest pixels in the scene, wherein the top percentage value is defined by a threshold value.

6. The computer-implemented method of claim 1 , further comprising:

generating video quality enhancement data based on the histogram data associated with the first video signal, and

wherein the converting the first video signal comprises:

converting the first video signal based on the video quality enhancement data.

7. The computer-implemented method of claim 6 , wherein the video quality enhancement data comprises dark scene adjustment data, bright scene adjustment data, or detail enhancement data.

8. A system for dynamic tone mapping of video content, comprising:

one or more memories; and

at least one processor each coupled to at least one of the memories and configured to perform operations comprising:

receiving histogram data associated with a first video signal representing a video program, wherein the first video signal has a first dynamic range and static metadata describing one or more brightness characteristics of the video program, wherein the histogram data comprises color values for a plurality of frames in the first video signal outputted by a display device;

determining a cumulative histogram for a scene in the video program based on the histogram data;

determining a near-brightest pixel for the scene in the video program based on the cumulative histogram, wherein the near-brightest pixel is a representative pixel value that defines a maximum target brightness value for proper display of the scene;

modifying a tone mapping curve based on the near-brightest pixel and characteristics of the display device to generate a modified tone mapping curve; and

converting the first video signal based on the modified tone mapping curve to generate a second video signal having a second dynamic range that is less than the first dynamic range.

9. The system of claim 8 , wherein the modifying the tone mapping curve comprises:

modifying the tone mapping curve based on a user setting.

10. The system of claim 9 , wherein the operations further comprise:

adapting the second video signal to the user setting.

11. The system of claim 8 , wherein the modifying the tone mapping curve comprises:

temporally filtering the modified tone mapping curve.

12. The system of claim 8 , wherein the determining the near-brightest pixel for the scene in the video program comprises:

determining the near-brightest pixel for the scene in the video program by identifying, using the cumulative histogram, a pixel value in the scene that belongs to a top percentage value of brightest pixels in the scene, wherein the top percentage value is defined by a threshold value.

13. The system of claim 8 , wherein the operations further comprise:

generating video quality enhancement data based on the histogram data associated with the first video signal; and

wherein the converting the first video signal comprises:

converting the first video signal based on the video quality enhancement data.

14. The system of claim 13 , wherein the video quality enhancement data comprises dark scene adjustment data, bright scene adjustment data, or detail enhancement data.

Assignments (2)
SECURITY INTEREST Recorded Sep 18, 2024
From: ROKU, INC.
To: CITIBANK, N.A.
Reel/Frame 068982/0377 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2024
From: CHIU, SHENG YUAN; WU, KUNLUNG
To: ROKU, INC.
Reel/Frame 066401/0513 →
Continuity (3)
Continuation 18303376 · Apr 19, 2023
Continuation 17534613 · Nov 24, 2021
Related Publication 20240153052A1 · May 9, 2024
References Cited (79)
US 9064313B2 · Seshadrinathan et al. · 2015 [cited by applicant]
US 9111330B2 · Messmer et al. · 2015 [cited by applicant]
US 9177509B2 · Kerofsky et al. · 2015 [cited by applicant]
US 9270563B1 · Brouillette et al. · 2016 [cited by applicant]
US 9275605B2 · Longhurst et al. · 2016 [cited by applicant]
US 9300938B2 · Atkins · 2016 [cited by applicant]
US 9396526B2 · Chiu et al. · 2016 [cited by applicant]
US 9607364B2 · Xu et al. · 2017 [cited by applicant]
US 9607658B2 · Atkins et al. · 2017 [cited by applicant]
US 9679366B2 · Xu et al. · 2017 [cited by applicant]
US 9973723B2 · Guo et al. · 2018 [cited by applicant]
US 9984446B2 · Ha et al. · 2018 [cited by applicant]
US 10007412B2 · Tao et al. · 2018 [cited by applicant]
US 10009613B2 · Seifi et al. · 2018 [cited by applicant]
US 10056042B2 · Atkins et al. · 2018 [cited by applicant]
US 10104334B2 · Evans et al. · 2018 [cited by applicant]
US 10136074B2 · Tao et al. · 2018 [cited by applicant]
US 10148906B2 · Seifi et al. · 2018 [cited by applicant]
US 10176561B2 · Evans et al. · 2019 [cited by applicant]
US 10194127B2 · Atkins · 2019 [cited by applicant]
US 10242627B2 · Farrell et al. · 2019 [cited by applicant]
US 10271054B2 · Greenebaum et al. · 2019 [cited by applicant]
US 10397576B2 · Kadu et al. · 2019 [cited by applicant]
US 10402952B2 · Baar et al. · 2019 [cited by applicant]
US 10554942B2 · Park et al. · 2020 [cited by applicant]
US 10657631B2 · Yip et al. · 2020 [cited by applicant]
US 10659745B2 · Hirota et al. · 2020 [cited by applicant]
US 10664960B1 · Lee · 2020 [cited by applicant]
US 10733985B2 · Pereira et al. · 2020 [cited by applicant]
US 10755392B2 · Chen et al. · 2020 [cited by applicant]
US 10902567B2 · Mertens · 2021 [cited by applicant]
US 10915999B2 · Eto · 2021 [cited by applicant]
US 10916000B2 · Van Der Vleuten et al. · 2021 [cited by applicant]
US 10957024B2 · Mandal et al. · 2021 [cited by applicant]
US 11024017B2 · Cellier et al. · 2021 [cited by applicant]
US 11107204B2 · Unger et al. · 2021 [cited by applicant]
US 11145039B2 · Huang · 2021 [cited by examiner]
US 11170479B2 · Kim et al. · 2021 [cited by applicant]
US 11176646B2 · Tao et al. · 2021 [cited by applicant]
US 11182882B2 · Leleannec et al. · 2021 [cited by applicant]
US 11403741B2 · Kikuchi et al. · 2022 [cited by applicant]
US 11410343B2 · Urabe et al. · 2022 [cited by applicant]
US 11416974B2 · Park et al. · 2022 [cited by applicant]
US 11418817B2 · Ward et al. · 2022 [cited by applicant]
US 11445202B2 · Tourapis et al. · 2022 [cited by applicant]
US 11445708B2 · Kim et al. · 2022 [cited by applicant]
US 11538136B2 · Yun et al. · 2022 [cited by applicant]
US 11734806B2 · Chiu et al. · 2023 [cited by applicant]
US 11769234B2 · Li et al. · 2023 [cited by applicant]
US 11803948B2 · Atkins et al. · 2023 [cited by applicant]
US 11908112B2 · Chiu · 2024 [cited by applicant]
US 20060262363A1 · Henley · 2006 [cited by examiner]
US 20160358319A1 · Xu et al. · 2016 [cited by applicant]
US 20160360171A1 · Tao et al. · 2016 [cited by applicant]
US 20160381335A1 · Tao et al. · 2016 [cited by applicant]
US 20160381363A1 · Tao et al. · 2016 [cited by applicant]
US 20170186141A1 · Ha et al. · 2017 [cited by applicant]
US 20170256039A1 · Hsu · 2017 [cited by examiner]
US 20170272690A1 · Seifi et al. · 2017 [cited by applicant]
US 20170330312A1 · Nam · 2017 [cited by applicant]
US 20180007356A1 · Kadu et al. · 2018 [cited by applicant]
US 20180167597A1 · Seifi et al. · 2018 [cited by applicant]
US 20190019277A1 · Chen et al. · 2019 [cited by applicant]
US 20190244333A1 · Choi · 2019 [cited by examiner]
US 20190313005A1 · Kuang et al. · 2019 [cited by applicant]
US 20200134792A1 · Mandal · 2020 [cited by examiner]
US 20200402216A1 · Kim et al. · 2020 [cited by applicant]
US 20220067893A1 · Kim et al. · 2022 [cited by applicant]
US 20220164930A1 · Kim et al. · 2022 [cited by applicant]
US 20220318964A1 · Kim et al. · 2022 [cited by applicant]
US 20220358627A1 · Deng et al. · 2022 [cited by applicant]
US 20230054046A1 · Xu et al. · 2023 [cited by applicant]
US 20230114798A1 · Nossek · 2023 [cited by examiner]
US 20230117976A1 · Woodall · 2023 [cited by applicant]
US 20230162334A1 · Chiu et al. · 2023 [cited by applicant]
US 20230289932A1 · Chiu et al. · 2023 [cited by applicant]
US 20230325987A1 · Wang · 2023 [cited by applicant]
US 20240221136A1 · Xu · 2024 [cited by examiner]
U.S. Appl. No. 17/534,613, filed Nov. 24, 2021, 61 pages. [cited by applicant]