WO2014172221A1 - Extracting true color from a color and infrared sensor - Google Patents

Extracting true color from a color and infrared sensor Download PDF

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Publication number
WO2014172221A1
WO2014172221A1 PCT/US2014/033909 US2014033909W WO2014172221A1 WO 2014172221 A1 WO2014172221 A1 WO 2014172221A1 US 2014033909 W US2014033909 W US 2014033909W WO 2014172221 A1 WO2014172221 A1 WO 2014172221A1
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Prior art keywords
data
green
red
infrared
blue
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PCT/US2014/033909
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English (en)
French (fr)
Inventor
Sing Bing Kang
Adam G. KIRK
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Microsoft Corp
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Microsoft Corp
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Priority to CN201480021958.7A priority Critical patent/CN105230003B/zh
Priority to EP14726261.2A priority patent/EP2987320B1/en
Publication of WO2014172221A1 publication Critical patent/WO2014172221A1/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Definitions

  • Some contemporary imaging devices contain multi-component sensors comprising color (R, G, B) and infrared photosites (where R, G and B are sometimes used herein for red, green and blue, respectively, and IR for infrared).
  • R, G, B infrared photosites
  • IR infrared
  • the R, G, and B part of the photosites referred to as Ro, Go, Bo hereinafter where the subscript zero represents the component state as initially captured
  • IR component such as when ambient light contains IR, or when IR is projected into a scene for depth sensing or other purposes.
  • ground truth color data is captured as raw image data via a sensor comprised of photosites.
  • the ground truth color data is also captured as long-pass-filtered image data via the sensor capturing through a long pass filter.
  • the long-pass-filtered image data for at least one of the red, green or blue parts of a photosite of the sensor are subtracted from the raw image data for each corresponding part of the photosite to obtain true color data values for the photosite.
  • Data corresponding to the true color data values are used to produce one or more tables or curves that are accessible during online usage to color correct an image.
  • a sensor comprising photosites having infrared, red, green, and blue parts is configured to capture a first image of ground truth data without a filter, capture a second image of the ground truth data with a long pass filter, and capture a third image of the ground truth data with a short pass filter.
  • a processing component obtains true red, green and blue data based upon the first and second images, and obtains true infrared data based upon the first and third images.
  • the processing component outputs data corresponding the true red, green and blue data and true infrared data into one or more tables or curves.
  • One or more aspects are directed towards (a) selecting a current infrared value, (b) accessing table or curve data to determine predicted red, green and blue values based upon the current infrared value, (c) accessing table or curve data to determine a predicted infrared value based upon the predicted red, green and blue values, (d) setting the current infrared value as the predicted infrared value, (e) returning to step (b) until a stopping criterion is met; and (f) outputting an infrared value and red green and blue values based upon the current infrared value and last predicted red, green and blue values.
  • FIGURES 1A and IB are block diagrams representing example cameras configured to color correct for infrared contamination of red, green and blue photosites, according to one or more example implementations.
  • FIG. 2 is a representation of an example color correction calibration procedure based upon capturing images via long pass filtering versus non-filtering, according to one or more example implementations.
  • FIG. 3 is a representation of an example color correction calibration procedure based upon capturing images via long pass filtering versus non- filtering, and short pass filtering versus non- filtering, according to one or more example implementations.
  • FIG. 4 is a flow diagram representing example steps that may be taken as part of offline color correction calibration, according to one or more example implementations.
  • FIG. 5 is a flow diagram representing example steps that may be taken as part of color correction during online image processing, according to one or more example implementations .
  • FIG. 6 is a block diagram representing an exemplary non-limiting computing system or operating environment, in the form of a gaming system, into which one or more aspects of various embodiments described herein can be implemented.
  • Various aspects of the technology described herein are generally directed towards extracting true RGB from sensor data. In one aspect, this is facilitated by a calibration process, e.g., using ground truth colors (e.g., a color chart) to determine how a specific camera or the like captures R, G, B and IR values in the presence of IP
  • true is an inexact, relative concept, and thus the calibration is based upon whatever is decided as ground truth, subject to varying lighting conditions and the like. Further, curves, tables, mappings and/or other structures and the like described below may use approximations, interpolations and so forth, whereby “true” typically means approximately achieving or approaching the ground truth, e.g., to the extent possible. In practice, significant improvement in image appearance has been obtained by outputting true color after compensating for IR.
  • any of the examples herein are non-limiting.
  • the examples herein are directed towards “true” RGB being approximated using IR component data
  • "true” IR may be approximated using RGB component data.
  • the present invention is not limited to any particular embodiments, aspects, concepts, structures, functionalities or examples described herein. Rather, any of the embodiments, aspects, concepts, structures, functionalities or examples described herein are non-limiting, and the present invention may be used various ways that provide benefits and advantages in image processing in general.
  • FIG. 1A shows an example system in which an RGB and IR camera 102 processes an image into true color, and optionally true IR.
  • a source e.g., raw
  • a true color extraction algorithm 108 (described below) into a true color, and optionally true IR image 110.
  • the true color extraction algorithm 108 uses tables / curves 112 (and/or other data) computed during an earlier calibration procedure.
  • the camera may be coupled to an external computing device to perform the processing, e.g., feeding raw images to the computing device for IR correction, with the true color / IR image used thereafter as desired.
  • FIG. IB is similar to FIG. 1 A, except that instead of memory or other computer- readable storage and executable processor instructions, instances of the tables / curves 120 (and/or other data) and algorithm 122 are coded into logic 124 as data and instructions, respectively.
  • the logic 124 executes the instructions to convert a raw (source) image 126 into a true color / IR image 128.
  • a source image is sometimes referred to as a "raw” image as if captured "as is" regardless of any other image processing.
  • FIG. 2 shows an example calibration process, which, for example may be part of the manufacturing process, or performed at a later time on any camera that has the suitable hardware, firmware and/or software capabilities to implement the algorithm / logic.
  • the same camera 222 is used to take (at least one) image of a ground truth color data, such as a fixed color chart 224.
  • a ground truth color data such as a fixed color chart 224.
  • FIG. 2 dashed instances of) the camera 222 are shown at two different "positions" 222 ⁇ and 222 ⁇ 2 representing two different times, but in reality the camera 222 is not moved, and is generally centered in front of the color chart 224. The difference is not in physical camera position, but rather that at time T2, a low pass filter 226 is placed in front of the camera to block visible light unlike at time T 1.
  • the color chart may, for example, be any known set of differently-colored patches or the like, but in one implementation was a six column by four-column grid of twenty- four different colors (including black white and gray variations). Each color in the grid corresponded to fixed, known R, G and B values.
  • An IR light source 228 may be used to project a consistent level of IR onto the color chart 224, generally under controlled lighting conditions. As described below, the IR light source may be variable so that different amounts of IR may be emitted for different types of calibration, or different IR light sources may be used. Note that the IR light source may be centered (e.g., slightly above or below) the camera at a suitable distance so that the color chart is illuminated relatively evenly. Notwithstanding, the amount of IR is determined at a per-pixel level and subtracted out in one implementation, whereby reasonable variations in the IR value across the color chart are not significant.
  • infrared or near infrared, NIR, which is synonymous with IR as used herein
  • NIR near infrared
  • the output may be generated using a "demosaicing" process as shown by block 230 in FIG. 2.
  • the photosites 232 and 233 contains the values captured with no filter and with the long pass filter that blocks visible light, respectively.
  • the non- filtered (raw) photosite 232 comprises IR, and R, G, and B values contaminated with some amount of IR, shown as R+IRR, G+IRG, and B+IRB.
  • the long-pass-filtered photosite 233 contains IR, IRR, IRG, IRB values.
  • a processing component 2366 subtracting the filtered IR from each of the raw R, G and B parts removes the difference ( ⁇ ) that the IR contamination is contributing:
  • the first part of the above equation corresponds to R ⁇ , G ⁇ B ⁇ , which can be linearized through radiometric calibration, for example, which is a known technique in image processing to compensate for sensors' non- linear response to light.
  • the non- linearity may be modeled in any of many known ways, e.g., empirically determined via various images captured in different lighting conditions.
  • an affine matrix transform may be offline computed for performing true RGB correction, which may then be used "online” in actual usage.
  • the following describes the transform, which may be modeled as lookup tables / curves (e.g., corresponding to blocks 237-239 in FIG. 2); (assuming some belief of IR leakage; because the camera has or, the information from that sensor also may be used):
  • the IR component may be ignored, whereby a 3> ⁇ 3 matrix may be used.
  • the calibration technique can be modified to use an additional set of images with a short-pass filter 336 (SPF) to block the IR, in addition to the long-pass filter (LPF) to block this visible light.
  • SPPF short-pass filter 336
  • LPF long-pass filter
  • This calibration configuration in FIG. 3 also has the same camera used at three different times, namely to capture raw, long-pass-flltered and short-pass-flltered images; (however a "solid-line” camera is not shown in FIG. 3 as in FIG. 2 to keep the FIG. 3 simple).
  • the capturing is shown via steps 402, 404 and 406.
  • the boxed "IR” (when the long pass filter is used) in photosite 233, and boxed "R”, "G”, and “B” (when the short pass filter is used) in photosite 334, represent the true signals to recover.
  • subtraction in block 336 of FIG. 3
  • subtraction may be used to remove the IR component from the R, G and B (step 408), along with (in this alternative) subtraction to remove the R, G and B components (step 410).
  • Linearization (also represented in block 336) is then performed at step 412.
  • "true” RGB may be used to predict RGBIR.
  • a mapping C may be used to map RGB to RGBIR (three dimensions to one dimension).
  • “true” IR may be used to predict IRR, IRG, IRB (three one-to-one mappings: “true” IR to IRR, “true” IR to IRG, “true” IR to IRB).
  • Each mapping can be in a form of lookup tables or fitted parametric curves (referred to as tables / curves QR, QG, QB), shown in FIG. 3 as block 337. The 3x4 (or 3> ⁇ 3) transform is not shown again.
  • IRo IR + RGBIR
  • Step 504 Use IR, QR, QG and QB to predict IRR, IRG, IRB.
  • Step 506 Compute R, G, B from IRR, IRG, IRB :
  • R Ro - IRR
  • G Go - IRG
  • B Bo - IRB.
  • Step 508 Use R, G, B and mapping C to predict RGBIR.
  • Step 512 repeats the process from step 504 until convergence (e.g., the updated IR value does not change over some number of iterations), or for a fixed number of steps.
  • Step 514 outputs the computed true values.
  • this process iteratively hones in on the true values by predicting the IR component to predict a closer true R, G, B and uses those predicted R, G, B values to find a closer IR value, which is used to find even closer R, G, B values and so on, until some convergence is reached or some iteration limit is reached.
  • the process may be repeated for each photosite. The process can be done in the other order, that is, by starting with RGB values and predicting IR, then updating the RGB with the predicted IR and so on.
  • IR illumination may be changed via a variable or multiple IR light sources; filters may or may not be used.
  • the calibration thus captures the color chart under different IR lighting conditions.
  • the different IR lighting conditions allow effective separation of true color from the IR component.
  • the linearization may done via lookup tables generated using a standard technique involving multiple exposures, while the matrix transform M 3 x 4 is extracted through the calibration process involving a color chart. Since there is no ground-truth for NIR when no filters are used, the data may be used as-is and directly interpolated.
  • calibration may be performed under different lighting conditions, with a different affine matrix computed for each lighting condition.
  • one lighting condition may be general room lighting, another may be dark room with some IR lighting, and so forth. It may also may be desirable (or needed) to have multiple affine transforms for the same lighting condition, split based on an amount of IR that is present.
  • a broad spectral distribution (or user input) may be used to estimate the current lighting condition, and the estimated lighting condition used to select the matching calibration parameters to apply.
  • An option is to compute a weighting scheme based on a similarity measure between the current lighting condition and the predefined ones, and weight average the pixel values as output.
  • FIG. 6 illustrates an example of a suitable computing and networking
  • the computing system environment 600 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the computing environment 600 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the example operating environment 600.
  • the invention is operational with numerous other general purpose or special purpose computing system environments or configurations.
  • Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the invention include, but are not limited to: personal computers, server computers, handheld or laptop devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
  • the invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer.
  • program modules include routines, programs, objects, components, data structures, and so forth, which perform particular tasks or implement particular abstract data types.
  • the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
  • program modules may be located in local and/or remote computer storage media including memory storage devices.
  • an example system for implementing various aspects of the invention may include a general purpose computing device in the form of a computer 610.
  • Components of the computer 610 may include, but are not limited to, a processing unit 620, a system memory 630, and a system bus 621 that couples various system components including the system memory to the processing unit 620.
  • the system bus 621 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures.
  • bus architectures include Industry Standard
  • ISA Industry Definition Bus
  • MCA Micro Channel Architecture
  • EISA Enhanced ISA
  • VESA Video Electronics Standards Association
  • PCI Component Interconnect
  • the computer 610 typically includes a variety of computer-readable media.
  • Computer-readable media can be any available media that can be accessed by the computer 610 and includes both volatile and nonvolatile media, and removable and nonremovable media.
  • Computer-readable media may comprise computer storage media and communication media.
  • Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable
  • Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, solid-state device memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by the computer 610.
  • Communication media typically embodies computer- readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
  • modulated data signal means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
  • communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of the any of the above may also be included within the scope of computer-readable media.
  • the system memory 630 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 631 and random access memory (RAM) 632.
  • ROM read only memory
  • RAM random access memory
  • BIOS basic input/output system
  • RAM 632 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 620.
  • FIG. 6 illustrates operating system 634, application programs 635, other program modules 636 and program data 637.
  • the computer 610 may also include other removable/non-removable,
  • FIG. 6 illustrates a hard disk drive 641 that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive 651 that reads from or writes to a removable, nonvolatile magnetic disk 652, and an optical disk drive 655 that reads from or writes to a removable, nonvolatile optical disk 656 such as a CD ROM or other optical media.
  • a hard disk drive 641 that reads from or writes to non-removable, nonvolatile magnetic media
  • a magnetic disk drive 651 that reads from or writes to a removable, nonvolatile magnetic disk 652
  • an optical disk drive 655 that reads from or writes to a removable, nonvolatile optical disk 656 such as a CD ROM or other optical media.
  • a removable, nonvolatile optical disk 656 such as a CD ROM or other optical media.
  • removable/non-removable, volatile/nonvolatile computer storage media that can be used in the example operating environment include, but are not limited to, magnetic tape cassettes, solid-state device memory cards, digital versatile disks, digital video tape, solid-state RAM, solid-state ROM, and the like.
  • the hard disk drive 641 is typically connected to the system bus 621 through a non-removable memory interface such as interface 640, and magnetic disk drive 651 and optical disk drive 655 are typically connected to the system bus 621 by a removable memory interface, such as interface 650.
  • the drives and their associated computer storage media provide storage of computer-readable instructions, data structures, program modules and other data for the computer 610.
  • hard disk drive 641 is illustrated as storing operating system 644, application programs 645, other program modules 646 and program data 647. Note that these components can either be the same as or different from operating system 634, application programs 635, other program modules 636, and program data 637.
  • Operating system 644, application programs 645, other program modules 646, and program data 647 are given different numbers herein to illustrate that, at a minimum, they are different copies.
  • a user may enter commands and information into the computer 610 through input devices such as a tablet, or electronic digitizer, 664, a microphone 663, a keyboard 662 and pointing device 661, commonly referred to as mouse, trackball or touch pad.
  • Other input devices not shown in FIG. 6 may include a joystick, game pad, satellite dish, scanner, or the like.
  • These and other input devices are often connected to the processing unit 620 through a user input interface 660 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB).
  • a monitor 691 or other type of display device is also connected to the system bus 621 via an interface, such as a video interface 690.
  • the monitor 691 may also be integrated with a touch-screen panel or the like. Note that the monitor and/or touch screen panel can be physically coupled to a housing in which the computing device 610 is incorporated, such as in a tablet-type personal computer. In addition, computers such as the computing device 610 may also include other peripheral output devices such as speakers 695 and printer 696, which may be connected through an output peripheral interface 694 or the like.
  • the computer 610 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 680.
  • the remote computer 680 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 610, although only a memory storage device 681 has been illustrated in FIG. 6.
  • the logical connections depicted in FIG. 6 include one or more local area networks (LAN) 671 and one or more wide area networks (WAN) 673, but may also include other networks.
  • LAN local area network
  • WAN wide area network
  • Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.
  • the computer 610 When used in a LAN networking environment, the computer 610 is connected to the LAN 671 through a network interface or adapter 670.
  • a network interface or adapter 670 When used in a WAN
  • the computer 610 typically includes a modem 672 or other means for establishing communications over the WAN 673, such as the Internet.
  • the modem 672 which may be internal or external, may be connected to the system bus 621 via the user input interface 660 or other appropriate mechanism.
  • a wireless networking component 674 such as comprising an interface and antenna may be coupled through a suitable device such as an access point or peer computer to a WAN or LAN.
  • program modules depicted relative to the computer 610, or portions thereof may be stored in the remote memory storage device.
  • FIG. 6 illustrates remote application programs 685 as residing on memory device 681. It may be appreciated that the network connections shown are examples and other means of establishing a communications link between the computers may be used.
  • An auxiliary subsystem 699 (e.g., for auxiliary display of content) may be connected via the user interface 660 to allow data such as program content, system status and event notifications to be provided to the user, even if the main portions of the computer system are in a low power state.
  • the auxiliary subsystem 699 may be connected to the modem 672 and/or network interface 670 to allow communication between these systems while the main processing unit 620 is in a low power state.

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US9928420B2 (en) 2018-03-27
US9760770B2 (en) 2017-09-12
EP2987138A1 (en) 2016-02-24
US20140307098A1 (en) 2014-10-16
US10268885B2 (en) 2019-04-23
CN105230003A (zh) 2016-01-06
CN105229411B (zh) 2019-09-03
EP2987323B1 (en) 2020-10-21
JP6469080B2 (ja) 2019-02-13
EP2987131A1 (en) 2016-02-24
EP2987320B1 (en) 2021-02-03
CN105229696A (zh) 2016-01-06
CN105210112B (zh) 2019-08-30
CN105210112A (zh) 2015-12-30
US10929658B2 (en) 2021-02-23
CN105229412B (zh) 2018-12-07
WO2014172223A1 (en) 2014-10-23
WO2014172228A1 (en) 2014-10-23
CA2907895A1 (en) 2014-10-23
EP2986936A1 (en) 2016-02-24
US20230332886A1 (en) 2023-10-19
CN105143817A (zh) 2015-12-09
US9508003B2 (en) 2016-11-29
MX2015014577A (es) 2017-02-15
US20140307055A1 (en) 2014-10-16
US20180218210A1 (en) 2018-08-02
WO2014172276A1 (en) 2014-10-23
EP3757510A1 (en) 2020-12-30
US10928189B2 (en) 2021-02-23
BR112015025819A8 (pt) 2019-12-24
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US20140309764A1 (en) 2014-10-16
EP2986935A1 (en) 2016-02-24
US12305974B2 (en) 2025-05-20
WO2014172229A1 (en) 2014-10-23
EP2986935B1 (en) 2021-03-31
US20150078672A1 (en) 2015-03-19
CN105247859A (zh) 2016-01-13
CN105229411A (zh) 2016-01-06
AU2014254219B2 (en) 2017-07-27
US20140307058A1 (en) 2014-10-16
KR20150140841A (ko) 2015-12-16
WO2014172222A1 (en) 2014-10-23
WO2014172231A1 (en) 2014-10-23
RU2663329C2 (ru) 2018-08-03
CN105229412A (zh) 2016-01-06
US20180260623A1 (en) 2018-09-13
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EP2987138B1 (en) 2021-09-22

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