System, method, and computer program product for detection limit determination for hyperspectral imaging

Abstract

Systems, methods, and computer program products for thermal contrast determination are provided. An example imaging system includes a first infrared (IR) imaging device that generates first IR image data of a field of view of the first IR imaging device, and a computing device connected with the first IR imaging device. The computing device receives temperature probe data from a temperature probe indicative of an external environment of the imaging system, and receives the first IR image data from the first IR imaging device. The computing device determines background temperature data based on the first IR image data, determines gas temperature data based on the probe temperature data, and determines a thermal contrast for each pixel based on a comparison between the background temperature data and the gas temperature data. The computing device further determines a detection limit for each pixel as a function of the thermal contrast.

Description

Technical Field

[0001] Exemplary embodiments of this disclosure generally relate to imaging systems, and more specifically, to hyperspectral and / or infrared (IR) imaging for detecting and quantifying gas leaks. Background Technology

[0002] In many environments, such as manufacturing facilities, drilling sites, pipelines, and / or similar environments, gases may be used and stored, transferred, moved, etc. For example, natural gas pipelines can transport natural gas (e.g., methane and / or the like) between two locations. During transport, some gas may be released from such exemplary pipelines, such as due to leaks in the pipeline system (e.g., due to poor sealing at pipe joints, impacts to the pipeline, etc.). To identify leaks and / or quantify the amount of gas emitted from such leaks (e.g., fugitive emissions), a hyperspectral camera can be used. The inventors have identified many deficiencies in the prior art in the art, and remedies for these deficiencies are the subject of the embodiments described herein. Summary of the Invention

[0003] As mentioned above, many industries and environments rely on or otherwise utilize gases in performing various operations related to these industries. For example, the natural gas industry extracts, transports, and processes natural gas (e.g., methane and / or similar substances) for subsequent use in generating heat, producing electricity, fueling vehicles, and so on. Such emissions of gases into the external environment, such as due to leaks in one or more systems, can result in significant product loss costs and substantial fines from, for example, government regulatory agencies. Furthermore, leaks of gases such as methane can pose hazardous conditions to workers or otherwise affect workplace safety. Therefore, accurate detection and quantification of gas leaks (e.g., gas plumes) are crucial for maximizing profits while preventing hazardous situations.

[0004] In infrared, hyperspectral, and / or thermal imaging applications used to detect or quantify gas leaks, the temperature associated with a specific location within an image (e.g., represented by one or more pixels) can indicate the temperature of any location, object, fluid, gas, etc., present or otherwise associated with that pixel. In other words, the temperature value or data associated with a particular pixel is affected by the temperature at each location along a line extending from the imaging device to the resolution limit of the device. Infrared (IR) imaging devices or cameras can determine the temperature of a particular pixel, which is influenced, for example, by the temperature of the leaking gas captured by the camera and associated with the particular pixel, as well as the temperature of the foreground / background of the pixel. Thus, the temperature of an exemplary background can operate to affect the camera's ability to properly quantify the presence or amount of gas at a particular location. Conventional systems attempting to detect and / or quantify gas leaks fail to adequately account for potential thermal contrasts (e.g., the temperature difference between the detected gas and the background), and / or fail to provide the user with an appropriate representation of the system's detection limits based on such thermal contrasts.

[0005] To address these and other issues, exemplary embodiments of the present disclosure can utilize infrared (IR) imaging devices (such as those implemented in hyperspectral camera embodiments) and various temperature probes (e.g., thermometers, thermistors, temperature sensors, etc.) to collect data indicating the temperature of a potential gas leak and the temperature associated with the background of the image. For example, and in the absence of a gas leak within the FOV of the exemplary IR imaging device, the gas temperature can be determined using probe temperature data by correlating the temperature trend of the gas leak to reach (e.g., match) the temperature of the external environment within an applicable time limit. In the absence of a gas leak, the IR image data can be used to determine or generate background temperature data, and the computing device described herein is operable to generate thermal contrast and exemplary detection limits based on a comparison between the gas temperature data and the background temperature data. Detection limit diagrams with corresponding visual identifiers can also be used to illustrate the detection limit of specific pixels for further user review. In this way, embodiments of the present disclosure can illustrate the evolution of environmental or surrounding conditions approaching a gas leak (e.g., fugitive emissions) to accurately detect and quantify the thermal detection capabilities of exemplary imaging systems (e.g., IR cameras, hyperspectral cameras, etc.).

[0006] Apparatus, methods, systems, devices, and associated computer program products for determining detection limits are provided. An exemplary imaging system may include a first infrared (IR) imaging device and a computing device configured to generate first IR image data of the field of view of the first IR imaging device, the computing device being operatively connected to the first IR imaging device. The computing device may be configured to receive probe temperature data (wherein the probe temperature data may indicate the external environment of the imaging system) from a temperature probe communicatively coupled to the computing device, and may receive the first IR image data from the first IR imaging device. The computing device may also determine background temperature data based on the first IR image data, wherein the background temperature data includes a first temperature for each of a plurality of pixels associated with the first IR image data. The computing device may further determine gas temperature data (wherein the gas temperature data includes a second temperature for each of a plurality of pixels associated with the first IR image data) based on the probe temperature data, and may determine the thermal contrast of each pixel based on a comparison between the background temperature data and the gas temperature data. The computing device may be further configured to determine the detection limit of each pixel based on the thermal contrast of each pixel.

[0007] In some implementations, the temperature probe may be located within the field of view of the first IR imaging device.

[0008] In some implementations, the imaging system includes a temperature probe that can be attached to a housing supporting the first IR imaging device.

[0009] In some embodiments, the imaging system may include a second infrared (IR) imaging device configured to generate second IR image data of the field of view of the second IR imaging device and operatively connected to the computing device. In such embodiments, the computing device may be further configured to determine background temperature data based on the second IR image data.

[0010] In some implementations, the computing device may be further configured to compare the detection limit of each pixel with a limit threshold. If the detection limit meets the limit threshold, the computing device may assign a first visual identifier to the corresponding pixel. If the detection limit fails to meet the limit threshold, the computing device may assign a second visual identifier to the corresponding pixel.

[0011] In some other embodiments, the computing device may be further configured to render a detection limit map that includes a visual representation of each pixel based on the visual identifier assigned to the corresponding pixel.

[0012] In other implementations, the computing device may be configured to modify the detection limit map in response to iterative determination of thermal contrast and associated determination of detection limits.

[0013] The above description of the invention is provided merely to outline some exemplary embodiments to provide a basic understanding of some aspects of this disclosure. Therefore, it should be understood that the above embodiments are merely examples and should not be construed as limiting the scope or substance of this disclosure in any way. It should be understood that, in addition to those summarized herein, the scope of this disclosure covers many possible embodiments, some of which will be further described below. Attached Figure Description

[0014] Some exemplary embodiments of this disclosure have been described in general terms above; reference will now be made to the accompanying drawings. In some embodiments described herein, the components shown in the drawings may or may not be present. Some embodiments may include fewer (or more) components than those shown in the figures.

[0015] Figure 1 Exemplary imaging systems utilizing emission sources are illustrated according to some exemplary embodiments described herein;

[0016] Figure 2 A schematic block diagram of an exemplary circuit capable of performing various operations according to some exemplary embodiments described herein is shown;

[0017] Figure 3 An exemplary flowchart for determining the detection limit is shown according to some exemplary embodiments described herein;

[0018] Figure 4 An exemplary flowchart for determining visual identity is shown according to some exemplary embodiments described herein;

[0019] Figure 5 Exemplary detection limit diagrams are shown according to some example implementations described herein; and

[0020] Figure 6 An exemplary flowchart for a specific implementation of multiple imaging devices according to some exemplary embodiments described herein is shown. Detailed Implementation

[0021] Some embodiments of this disclosure will be described more fully below with reference to the accompanying drawings, which illustrate some, but not all, embodiments of this disclosure. In fact, this disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided to enable this disclosure to meet applicable legal requirements. Throughout this document, similar reference numerals refer to similar elements. As used herein, the computing device of the exemplary imaging system may be referred to as an exemplary “device.” However, elements of the device described herein are equally applicable to methods and computer program products protected by the claims. Therefore, the use of any such term should not be construed as limiting the spirit and scope of the embodiments of this disclosure.

[0022] Definition of terminology

[0023] As used herein, the terms “data,” “content,” “information,” “electronic information,” “signal,” “command,” and similar terms are used interchangeably to refer to data capable of being transmitted, received, and / or stored according to embodiments of the present invention. Therefore, the use of any such terms should not be construed as limiting the substance or scope of embodiments of this disclosure. Furthermore, where the first device is described herein as receiving data from the second device, it should be understood that data can be received directly from the second device or indirectly via one or more intermediate computing devices (such as, for example, one or more servers, repeaters, routers, network access points, base stations, hosts, etc., sometimes referred to herein as a “network”). Similarly, where the first device is described herein as sending data to the second device, it should be understood that data can be sent directly to the second device or indirectly via one or more intermediate computing devices (such as, for example, one or more servers, remote servers, cloud-based servers (e.g., cloud tools), repeaters, routers, network access points, base stations, hosts, etc.).

[0024] As used herein, the term “comprising” means including but not limited to, and should be interpreted in the manner commonly used in the patent context. It should be understood that the use of broad terms such as “comprising,” “including,” and “having” provides support for narrower terms such as “consisting of,” “substantially composed of,” and “substantially constituted by.”

[0025] As used herein, phrases such as “in one embodiment,” “according to one embodiment,” and “in some embodiments” generally refer to a specific feature, structure, or characteristic that follows the phrase and may be included in at least one embodiment of this disclosure. Therefore, such specific feature, structure, or characteristic may be included in more than one embodiment of this disclosure, such that these phrases do not necessarily refer to the same embodiment.

[0026] As used herein, the term “exemplary” means “used as an example, instance, or illustration.” Any specific implementation described herein as an “example” is not necessarily to be construed as preferred or advantageous over other specific implementations.

[0027] As used herein, the terms "first IR imaging device" or "first IR imager" refer to one or more devices capable of generating first IR image data. Exemplary first IR imaging devices may include thermal imaging cameras, IR imagers, IR cameras, thermal imaging cameras, and / or similar devices capable of generating IR image data indicating the field of view (FOV) of the first IR imaging device. In other words, a first IR imaging device may include any device, apparatus, system, etc., capable of detecting infrared energy / radiation and converting that infrared energy / radiation into a corresponding electronic signal (e.g., first IR image data). As a non-limiting example, a first IR imaging device may include an IR camera configured to capture IR energy emitted by fugitive emissions from exemplary emission sources described below, located within a first FOV associated with the first IR imaging device. The first IR imaging device may also be associated with a first filter defining a first bandpass frequency (e.g., a device that allows frequencies within a certain range to pass and attenuates frequencies outside that range). As described below, the first filter can be configured to deliver IR radiation to a first IR imaging device having a frequency associated with a fugitive emission (e.g., a gas) (e.g., methane, etc.) that the imaging device is designed to monitor.

[0028] As used herein, the term "second IR imaging device" or "second IR imager" refers to one or more devices capable of generating second IR image data. Exemplary second IR imaging devices may also include thermal imaging cameras, IR imagers, IR cameras, thermal imaging cameras, and / or similar devices capable of generating IR image data indicating the field of view (FOV) of the second IR imaging device. In other words, a second IR imaging device may include any device, apparatus, system, etc., capable of detecting infrared energy / radiation and converting said infrared energy / radiation into corresponding electronic signals (e.g., second IR image data). As a non-limiting example, a second IR imaging device may also include an IR camera configured to capture IR energy emitted by fugitive emissions from an exemplary emission source described below, located within a second FOV associated with the second IR imaging device. The second IR imaging device may also be associated with a second filter (e.g., a device that allows frequencies within a certain range to pass and attenuates frequencies outside that range) defining a second bandpass frequency. As described below, the second filter may be configured to deliver IR radiation to a second IR imaging device having a frequency associated with the fugitive emissions (e.g., gases) (e.g., methane, etc.) that the imaging device is designed to monitor, and the second filter may be further configured to use the same frequency as the first filter. Although this disclosure refers to two (2) IR imaging devices, based on the intended application of the imaging system, the disclosure contemplates that the imaging system may include any number of IR imaging devices.

[0029] As used herein, the term "computing device" means any user equipment, controller, object, or system capable of physically or network-communicating with the first IR imaging device, the second IR imaging device, and / or the temperature probe described below. For example, a computing device may refer to a wireless electronic device configured to perform various IR image-related operations in response to first IR image data and / or second IR image data generated by the first IR imaging device and the second IR imaging device, respectively. The computing device may be configured to communicate with the first IR imaging device and / or the second IR imaging device via Bluetooth, NFC, Wi-Fi, 3G, 4G, 5G protocols, etc. In some cases, the computing device may include the first IR imaging device and / or the second IR imaging device (e.g., an integrated configuration).

[0030] As used herein, the terms "escape emission," "gas leak," "gas plume," and / or "gas leak plume" can refer to a collection of gas atoms or particles, wherein the individual atoms or particles are widely spaced. Such gases can leak or otherwise be emitted from a containment vessel (e.g., a natural gas pipeline, etc.) or an emission source, and can form a plume or column. The plume can be a vertical body of a first fluid (e.g., the leaking gas) that moves relative to or through another second fluid (e.g., ambient air). As will be apparent from this disclosure, the intensity of a gas can dissipate with increasing distance between the leaking gas and the leak source. For example, a gas leak from a pipeline containing methane gas can result in a gas plume of methane gas emitted from the pipeline, such that the intensity (e.g., concentration) of the methane gas decreases with increasing distance between the methane gas particles and the leak location. Although described herein with reference to exemplary methane gas applications, this disclosure contemplates that the imaging systems described herein can be configured for use with gases of any type, concentration, etc. Furthermore, and as described below, the temperature of the gas leak can reach or otherwise match the temperature of the external environment within an applicable time limit.

[0031] As used herein, the term "computer-readable medium" refers to non-transitory storage hardware, non-transitory storage device, or non-transitory computer system memory that can be accessed by a computing device, microcomputing device, computing system, or module of a computing system to encode computer-executable instructions or software programs thereon. A non-transitory "computer-readable medium" can be accessed by a computing system or module of a computing system to retrieve and / or execute computer-executable instructions or software programs encoded on that medium. Exemplary non-transitory computer-readable media may include, but are not limited to, one or more types of hardware memory, non-transitory tangible media (e.g., one or more magnetic storage disks, one or more optical disks, one or more USB flash drives), computer system memory, or random access memory (such as DRAM, SRAM, EDO RAM), etc.

[0032] After listing a series of necessary definitions throughout this application, exemplary system architectures and exemplary apparatuses for implementing exemplary embodiments and features of this disclosure are described below.

[0033] Device architecture and exemplary apparatus

[0034] refer to Figure 1An exemplary imaging system 100 is shown having a first IR imaging device 102 and a second IR imaging device 104, which are operatively connected to a computing device 200 via a network 106. As defined above, the first IR imaging device 102 may include a device capable of generating first IR image data and may be a thermal imaging camera, IR imager, IR camera, thermal imaging camera, and / or similar device. The first IR imaging device 102 may be associated with a field of view (FOV) 103. FOV 103 may refer to an observable area in which the first IR imaging device 102 can capture images (e.g., generate first IR image data). As described below, in some embodiments, the first IR imaging device 102 may be positioned or oriented such that the emission source 10 is physically located within the FOV 103 of the first IR imaging device 102. In other words, the FOV 103 of the first IR imaging device 102 allows the first IR image data generated by the first IR imaging device 102 (e.g., the IR image captured by the FOV 103) to include IR image data indicating the emission source 10 or otherwise associated with it. This disclosure contemplates that the first IR imaging device 102 can be positioned at any physical location and in any orientation based on the intended application of the system 100. Furthermore, this disclosure contemplates that the FOV 103 can vary based on the operating parameters of the first IR imaging device 102.

[0035] In some embodiments, the imaging system 100 may include a second IR imaging device 104, which may include a device capable of generating second IR image data and may be a thermal imaging camera, IR imager, IR camera, thermal imaging camera, and / or similar device. The second IR imaging device 104 may be associated with a field of view (FOV) 105. FOV 105 may refer to an observable area in which the second IR imaging device 104 can capture images (e.g., generate second IR image data). As described below, in some embodiments, the second IR imaging device 104 may be positioned or oriented such that the emission source 10 is physically located within the FOV 105 of the second IR imaging device 104. In other words, the FOV 105 of the second IR imaging device 104 may allow the second IR image data generated by the second IR imaging device 104 (e.g., IR images captured by the FOV 105) to include IR image data indicating the emission source 10 or otherwise associated with it. This disclosure envisions that the second IR imaging device 104 can be positioned at any physical location and in any orientation based on the intended application of system 100. Furthermore, this disclosure envisions that the field of view (FOV) 105 can vary based on the operating parameters of the second IR imaging device 104. As will be apparent from this disclosure, the first FOV 103 and the second FOV 105 can be different based on the different positions of the corresponding first IR imaging device 102 and second IR imaging device 104. In other embodiments, the first FOV 103 and the second FOV 105 can at least partially overlap or coincide.

[0036] In some embodiments as described herein, the first IR imaging device 102 and the second IR imaging device 104 may be formed as an integrated device, or may otherwise be housed together, such as via the housing 108 of the hyperspectral camera. In such embodiments, FOV 103 and FOV 105 may overlap, for example, at least partially as described above. In other embodiments, the first IR imaging device 102 and the second IR imaging device 104 may be positioned separately. In any embodiment, this disclosure contemplates that FOV 103 and / or FOV 105 may be dynamically adjusted (e.g., tilted, translated, pivoted, etc.) during the performance of the operations described herein.

[0037] See below for reference Figures 3 to 6As described in the operation, the imaging system 100 of this disclosure can be positioned close to the emission source 10 (e.g., from which gas may leak through a pipe or any feature, vessel, container, etc.) to detect and quantify the fugitive emissions 20 emitted from the emission source 10 (e.g., after completing the detection limit operation described herein). This positioning allows for the existence of a distance between the emission source 10 and the associated fugitive emissions 20. As will be apparent from the relative positions of the first IR imaging device 102 and the second IR imaging device 104, the first IR image data generated by the first IR imaging device 102 and the second IR image data generated by the second IR imaging device 104 may differ due to the different viewing angles (e.g., FOVs 103, 105) of these devices 102, 104. Therefore, the first set of features (e.g., geometric center, centroid, etc.) or features (e.g., corners, edges, contours, etc.) of the venting emissions 20 in the first IR image data may differ from the second set of features (e.g., geometric center, centroid, etc.) or features (e.g., corners, edges, contours, etc.) of the same venting emissions 20 in the second IR image data. See below for reference. Figure 6 The embodiments of this disclosure can utilize multiple sources of IR image data (e.g., first IR imaging device 102, second IR imaging device 104, etc.) to provide a robust solution for determining thermal contrast and detection limits. Therefore, any differences between the characteristics of the fugitive emissions 20 in the first IR image data and the characteristics of the fugitive emissions 20 in the second IR image data can be identified, described, or otherwise considered to ensure accurate determination of thermal contrast and detection limits.

[0038] The imaging system 100 may also include a temperature probe 110, which may be communicatively coupled to the computing device 200 and, in some embodiments, communicatively coupled to a first IR imaging device 102 and / or a second IR imaging device 104. The temperature probe 110 may be configured to generate probe temperature data indicating the temperature proximal to the temperature of the probe 110. By way of example, the temperature probe 110 may include a thermistor configured to generate probe temperature data indicating the temperature (e.g., air temperature) proximal to a probe, extension, or other part in fluid communication with the external environment of the imaging system 100 described herein. Although described herein with reference to thermistors, the invention contemplates that the temperature probe 110 may be non-limitingly used with any temperature sensor, thermocouple, thermometer, etc., capable of determining temperature (e.g., generating probe temperature data). In some embodiments, the imaging system 100 includes a temperature probe 100 attached to, housed in, or secured to a housing 108 that supports at least the first IR imaging device 102 (e.g., an integrated component embodiment). In other embodiments, the temperature probe 110 may be located within the field of view of the first IR imaging device 102 and / or near the emission source 10, as described below.

[0039] Continue to refer to Figure 1 The imaging system 100 may include a computing device 200 connected via a network 106 to a first IR imaging device 102, a second IR imaging device 104, and / or a temperature probe 110. In some cases, the first IR imaging device 102 may include all or part of the computing device 200. In some cases, the second IR imaging device 104 may include all or part of the computing device 200. In other cases, the first IR imaging device 102, the second IR imaging device 104, and the computing device 200 may be formed as a single integrated device. The computing device 200 may include circuitry, a network processor, etc., configured to perform some or all of the process described herein in a device-based (e.g., IR image-based) process, and may be any suitable processing device and / or network server. In this respect, the computing device 200 may be embodied by any of a variety of devices. For example, computing device 200 may be configured to receive / transmit data (e.g., IR image data, probe temperature data, etc.) and may include any terminal from a variety of fixed terminals, such as a server, desktop computer, or kiosk; or may include any mobile terminal from a variety of mobile terminals, such as a portable digital assistant (PDA), mobile phone, smartphone, laptop computer, tablet computer; or, in some embodiments, peripheral devices connected to one or more fixed or mobile terminals. The exemplary embodiments contemplated herein may have various form factors and designs, but will still include at least... Figure 2The components shown and described in conjunction with the figures. In some embodiments, computing device 200 may include several servers or computing devices performing interconnect and / or distributed functions. Although many arrangements are envisioned herein, computing device 200 is shown and described herein as a single computing device to avoid unnecessarily complicating this disclosure.

[0040] Network 106 may include one or more wired or wireless communication networks, including, for example, wired and / or wireless local area networks (LANs), personal area networks (PANs), metropolitan area networks (MANs), wide area networks (WANs), etc., and any hardware, software, and / or firmware (e.g., network routers, switches, hubs, etc.) used to implement the one or more networks. For example, network 106 may include cellular phones, mobile broadband, Long Term Evolution (LTE), GSM / EDGE, UMTS / HSPA, IEEE 802.11, IEEE 802.16, IEEE 802.20, Wi-Fi, dial-up, and / or WiMAX networks. Furthermore, network 106 may include public networks (such as the Internet), private networks (such as intranets), or combinations thereof, and may utilize various networking protocols currently available or developed in the future, including but not limited to TCP / IP-based networking protocols. In some embodiments, network 106 may refer to a collection of wired connections such that the first IR imaging device 102, the second IR imaging device 104, the temperature probe 110, and / or the computing device 200 can be physically connected via one or more network cables, etc.

[0041] like Figure 2 As shown, computing device 200 may include processor 202, memory 204, input / output circuitry 206, and communication circuitry 208. Furthermore, computing device 200 may include image processing circuitry 210 and / or machine learning circuitry 212. Computing device 200 may be configured to perform the following combined Figures 3 to 6 The operation described herein. While functional language is used in some cases to describe components 202 to 212, it should be understood that a particular specific implementation necessarily includes the use of specific hardware. It should also be understood that some components of these components 202 to 212 may include similar or common hardware. For example, both sets of circuits may use the same processor 202, memory 204, communication circuitry 208, etc., to perform their associated functions, so that each set of circuits does not require duplicate hardware. The use of the term "circuit" as used herein includes specific hardware configured to perform the functions associated with the corresponding circuits described herein. As described in the examples above, in some embodiments, various elements or components of the circuitry of computing device 200 may be housed within the first IR imaging device 102, the second IR imaging device 104, and / or the temperature probe 110. In this regard, it should be understood that some of the components described in connection with computing device 200 may be housed in Figure 1 The equipment is located within one or more devices, while other components are housed within another device within these devices, or are composed of... Figure 1 Another device not explicitly shown in the text.

[0042] Of course, while the term "circuit" should be broadly understood to include hardware, in some implementations, the term "circuit" may also include software used to construct the hardware. For example, although "circuit" may include processing circuitry, storage media, network interfaces, input / output devices, etc., other elements of the computing device 200 may provide or supplement the functionality of a particular circuit.

[0043] In some embodiments, processor 202 (and / or coprocessor or any other processing circuitry assisting or otherwise associated with the processor) may communicate with memory 204 via a bus for transferring information between components of computing device 200. Memory 204 may be non-transitory and may include, for example, one or more volatile and / or non-volatile memories. In other words, for example, memory may be an electronic storage device (e.g., a non-transitory computer-readable storage medium). Memory 204 may be configured to store information, data, content, applications, instructions, etc., for enabling computing device 200 to perform various functions according to exemplary embodiments of this disclosure.

[0044] Processor 202 can be embodied in a variety of different ways and may include, for example, one or more processing devices configured to execute independently. Alternatively, the processor may include one or more processors configured in series via a bus to enable independent execution of instructions, pipelines, and / or multiple threads. The term "processing circuitry" is understood to include single-core processors, multi-core processors, multiple processors within a computing device, and / or remote or "cloud" processors.

[0045] In an exemplary embodiment, processor 202 may be configured to execute instructions stored in memory 204 or otherwise accessible to processor 202. Alternatively or otherwise, processor 202 may be configured to perform hard-coded functions. Thus, whether configured by hardware or by a combination of hardware and software, processor 202 may represent an entity (e.g., physically embodied in circuit form) capable of performing operations according to embodiments of this disclosure. Alternatively, for example, when processor 202 embodies an executor of software instructions, these instructions may specifically configure processor 202 to perform the algorithms and / or operations described herein when executing these instructions.

[0046] The computing device 200 also includes input / output circuitry 206, which can then communicate with the processor 202 to provide output to a user and receive input from the user, user equipment, or another source. In this regard, the input / output circuitry 206 may include a display operable by a mobile application. In some embodiments, the input / output circuitry 206 may also include additional functionality, including a keyboard, mouse, joystick, touchscreen, touch area, softkeys, microphone, speaker, or other input / output mechanisms. The processor 202 and / or the user interface circuitry including the processor 202 may be configured to control one or more functions of the display via computer program instructions (e.g., software and / or firmware) stored in processor-accessible memory (e.g., memory 204, etc.).

[0047] The communication circuit 208 can be any device, such as a hardware or hardware and software combination embodied in a device or circuit configured to receive and / or transmit data to and / or to a network and / or to any other device, circuit, or module communicating with the computing device 200. In this regard, the communication circuit 208 may include, for example, a network interface for enabling communication with a wired or wireless communication network. For example, the communication circuit 208 may include one or more network interface cards, antennas, buses, switches, routers, modems, and supporting hardware and / or software, or any other device suitable for enabling communication via a network. Additionally or alternatively, the communication interface may include circuitry for interacting with one or more antennas to enable signal transmission via one or more antennas or to process signal reception received via one or more antennas. These signals may be transmitted by the computing device 200 using any of a variety of wireless personal area network (PAN) technologies, such as... Versions 1.0 to 3.0, Bluetooth Low Energy (BLE), infrared wireless (e.g., IrDA), ultra-wideband (UWB), inductive wireless transmission, etc. Furthermore, it should be understood that these signals can be transmitted using Wi-Fi, Near Field Communication (NFC), Global Microwave Access Interoperability (WiMAX), or other proximity-based communication protocols.

[0048] Image processing circuit 210 includes hardware components designed to analyze first IR image data and / or second IR image data to determine or generate background temperature data associated with each pixel within the first IR image data and / or second IR image data. Image processing circuit 210 may further determine the thermal contrast of each pixel based on a comparison between the background temperature data and gas temperature data, and determine the detection limit of each pixel based on the determined thermal contrast. Image processing circuit 210 may utilize processing circuitry such as processor 202 to perform its corresponding operations, and may utilize memory 204 to store the collected information. In some cases, image processing circuit 210 may also include machine learning circuitry 212, which includes hardware components designed to analyze IR image data using artificial intelligence, supervised learning, unsupervised learning, etc., to iteratively determine the thermal contrast and detection limit associated with the imaging system. By way of example, machine learning circuitry 212 may include or utilize artificial neural networks or convolutional neural networks trained at least on multiple captured IR image data and / or user confirmations associated with a gas leak or plume to improve subsequent operations of the operations described herein. The machine learning circuit 212 can also use processing circuits such as processor 202 to perform its corresponding operations, and can use memory 204 to store the collected information.

[0049] It should also be understood that, in some embodiments, the image processing circuitry 210 and / or the machine learning circuitry 212 may include separate processors, specially configured field-programmable gate arrays (FPGAs), or application-specific integrated circuits (ASICs) to perform their respective functions. Furthermore, computer program instructions and / or other types of code may be loaded onto a computer, processor, or other programmable circuitry to create a machine, such that the computer, processor, or other programmable circuitry executing the code on that machine forms means for implementing various functions, including those described in conjunction with the components of computing device 200.

[0050] As will be understood from the above and based on this disclosure, embodiments of this disclosure can be configured as apparatuses, systems, methods, etc. Therefore, embodiments may include various means, including entirely hardware or any combination of software and hardware. Furthermore, embodiments may take the form of a computer program product comprising instructions (e.g., computer software stored on a hardware device) stored on at least one non-transitory computer-readable storage medium. Any suitable computer-readable storage medium may be used, including non-transitory hard disks, CD-ROMs, flash memory, optical storage devices, or magnetic storage devices.

[0051] Exemplary detection limit determination

[0052] Figure 3 A flowchart is shown that includes a series of operations for determining an exemplary detection limit. As described above, Figure 3 The operations shown may be performed, for example, by a device (e.g., computing device 200), with the assistance of the device, and / or under the control of the device. In this regard, the execution of these operations may invoke one or more of the processor 202, memory 204, input / output circuitry 206, communication circuitry 208, image processing circuitry 210, and / or machine learning circuitry 212.

[0053] As shown in operation 305, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for receiving probe temperature data from temperature probe 110, wherein the probe temperature data indicates the external environment of imaging system 100. As described above, computing device 200 may be communicatively coupled to temperature probe 110 to receive probe temperature data in response to operation of temperature probe 110. In some embodiments, temperature probe 110 may be attached to housing 108 supporting first IR imaging device 102, such that the probe temperature data received at operation 305 relates to data entries indicating the air temperature near, around, or otherwise in the vicinity of housing 108. In other embodiments, temperature probe 110 may be detached from first IR imaging device 102, such that the probe temperature data received at operation 305 indicates the air temperature near, around, or otherwise in the vicinity of the relative position of temperature probe 110.

[0054] In other embodiments, the temperature probe 110 may be located within the FOV 103 of the first IR imaging device 102 and / or near the emission source 10. As will be apparent from this disclosure, the distance between the temperature probe 110 and the location where any gas leak or venting 20 may occur can operate to affect the applicability of the probe temperature data. However, given that the location of the emission source 10 may be unknown, the temperature probe 110 may be located at a location where venting 20 is more likely to occur (e.g., conduit inlets, valves, locations of previous leaks or emission events, etc.). Although Figure 1 A single temperature probe 110 is shown, but this disclosure contemplates that the imaging system 100 may include multiple temperature probes 110 at the same or different locations in order to generate probe temperature data from multiple locations, for example, within the FOV 103.

[0055] As shown in operation 310, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, and image processing circuitry 210 for receiving first IR image data associated with the field of view 103 of the first IR imaging device 102 from the first infrared (IR) imaging device 102. The first IR image data generated by the first IR imaging device 102 may include multiple data entries, one or more of which may be associated with a specific pixel representing the FOV 103 of the first IR imaging device 102. Figure 1 As shown, the first IR image data may include one or more data entries associated with emission source 10 to include background that may be present during an emission event (e.g., the presence of fugitive emission 20). In other words, the first IR image data received at operation 310 may refer to IR image data generated by the first IR imaging device 102 in the absence of fugitive emission 20. For example, the first IR image data may indicate the intensity of IR radiation received by the first IR imaging device 102 for each pixel captured for FOV 103 (including those pixels associated with the background of potential emission source 10). As will be apparent from this disclosure, the first IR image data may occur (e.g., be generated) in the absence of fugitive emission 20 in order to determine a background temperature unaffected by the temperature associated with such potential fugitive emission 20. For this purpose, the imaging system 100 may employ various image processing techniques to determine that FOV 103 lacks fugitive emission 20 at the time the first IR image data is generated.

[0056] In embodiments where a computing device 200 and a first IR imaging device 102 are housed within a common or integrated device (e.g., the computing device 200 includes the first IR imaging device 102), first IR image data may be received by the computing device 200 as part of the normal operation of the first IR imaging device 102 (e.g., internally transmitted, if any). In other embodiments where the computing device 200 and the first IR imaging device 102 are located separately (e.g., connected via network 106), the computing device 200 may be configured to receive first IR image data from the first IR imaging device 102 in response to the generation of first IR image data. In other words, each instance of the first IR image data generation may be transmitted to the computing device 200 after generation. In other embodiments, the computing device 200 may periodically (e.g., according to a defined rate or sampling protocol) request first IR image data from the first IR imaging device 102.

[0057] As shown in operation 315, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for determining or generating background temperature data based on the first IR image data. The background temperature data may include a first temperature for each of a plurality of pixels associated with the first IR image data. As described above, the first IR image data may include data entries indicating the intensity of IR radiation received by the first IR imaging device 102 for a plurality of pixels representing the FOV 103, such that this intensity can be used to determine the associated temperature (e.g., a first temperature) for each of the plurality of pixels associated with the first IR image data. As will be apparent from this disclosure, the first IR image data received at operation 310 may refer to a hyperspectral image cube, wherein a given x / y position or location in a conventional red / blue / green (RGB) vision camera also includes various IR radiation values ​​(e.g., λ1, λ2, etc.) indicating the intensity of IR radiation received by the first IR imaging device 102 for each pixel captured for the FOV 103. In some implementations, the first temperature for each pixel may refer to a temperature value, a temperature range, etc.

[0058] Subsequently, as shown in operation 320, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, machine learning circuitry 212, etc., for determining gas temperature data based on probe temperature data. The gas temperature data may include a second temperature for each of a plurality of pixels associated with the first IR image data. As described above, temperature probe 110 may generate probe temperature data indicative of the external environment of imaging system 100. Furthermore, although an emission event (e.g., a gas leak) may cause a temperature rise at the initial emission of gas, due to applicable time constraints, the temperature of the gas leak (e.g., the emission event) may reach or otherwise substantially match the temperature of the external environment. Therefore, embodiments of this disclosure may set an exemplary gas temperature (e.g., the temperature associated with a potential fugitive emission 20) as the temperature of the external environment provided by the probe temperature data.

[0059] In some implementations, a second temperature may be assigned to each of a plurality of pixels associated with the first IR image data, using the same temperature value or temperature range as provided by temperature probe 110. In implementations where a plurality of temperature probes 110 may be used as described above, computing device 200 may, at operation 320, determine gas temperature data by selectively associating probe temperature data with pixels in the first IR image data. For example, computing device 200 may receive data entries indicating the relative position of temperature probe 110 within FOV 103 via imaging processing, user input, etc. Therefore, computing device 200 may determine the relative distance between a particular pixel and the plurality of temperature probes 110, and assign the second temperature value of that particular pixel as the temperature value defined by the probe temperature data generated by the temperature probe 110 that is physically closest to that particular pixel.

[0060] Subsequently, as shown in operation 325, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, machine learning circuitry 212, etc., for determining the thermal contrast of each pixel based on a comparison between background temperature data and gas temperature data. As described above, the background temperature data may include a first temperature value for each of a plurality of pixels associated with the first IR image data. Similarly, the gas temperature data may include a second temperature value for each of a plurality of pixels associated with the first IR image data notified by probe temperature data. Thus, in some embodiments, the determination of the thermal contrast at operation 325 may refer to a pixel-by-pixel mathematical difference between the background temperature and the gas temperature (e.g., a mathematical difference between the first temperature value and the second temperature value for each pixel). As will be apparent from this disclosure, a positive thermal contrast value may refer to a situation in which the escaping gas 20 absorbs energy (e.g., heat), while a negative thermal contrast value may refer to a situation in which the escaping gas 20 emits energy (e.g., heat). Therefore, in some implementations, the thermal contrast value of each pixel may refer to the absolute value of the mathematical difference between a first temperature value and a second temperature value of each pixel.

[0061] Subsequently, as shown in operation 330, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, machine learning circuitry 212, etc., for determining a detection limit for each pixel based on the thermal contrast of each pixel. The detection limit for each pixel is operable to instruct the user on the ability of the imaging system 100 to appropriately detect and / or quantify the vent emissions 20 at a specific location (e.g., a specific pixel). For example, the ability to detect vent emissions 20 may decrease as thermal contrast increases, and / or the ability to quantify the size, intensity, amount, etc., of vent emissions may decrease. In a particular example, a relatively large thermal contrast value may be provided for pixels associated with a background location aligned with a furnace or other heat source, while a relatively small thermal contrast value may be presented for pixels associated with a background location aligned with a cooling or relatively low-temperature location. In such examples, the ability of the IR imaging system 100 to quantify vent emissions 20 aligned with an exemplary heat source may be reduced relative to the ability of the IR imaging system 100 to quantify vent emissions 20 aligned with a low-temperature location. Such detection limits can be provided to the user in the form of a detection limit diagram as described below, so as to indicate to the user the detection capability of the imaging system 110 with respect to a particular pixel (e.g., a particular location).

[0062] As will be apparent from this disclosure, the first IR image data received by computing device 200 may refer to a hyperspectral image cube, wherein a given x / y position or location in a conventional red / blue / green (RGB) vision camera also includes various IR radiation values ​​(e.g., λ1, λ2, etc.), which indicate the intensity of IR radiation received by first IR imaging device 102 for each pixel captured for FOV 103. To determine the detection limits as described herein, computing device 200 may utilize one or more radiation transfer models. A radiation model may refer to energy transfer in the form of electromagnetic radiation that propagates through the environment and is affected by absorption, emission, and / or scattering. As will be apparent from this disclosure, spectral absorption data may refer to the spectrum of absorption lines, absorption bands, etc., formed by radiation (e.g., light) produced by a heating source (e.g., where there is a temperature difference with the surrounding environment of the source). A source producing a continuous spectrum (e.g., fugitive emission 20) passes through a relatively cool gas, and the associated absorption spectrum indicates the portion of incident electromagnetic radiation absorbed by the material within a frequency range. Such spectra associated with spectral absorption data can be used, as described in operation 330, to determine the detection limit of a particular pixel based on an exemplary radiative transfer model. In other words, there exists a function for the exemplary radiative transfer model that can be expressed as path concentration based on thermal contrast.

[0063] Figure 4 A flowchart is shown, comprising a series of operations for visual identity determination. As described above, Figure 4 The operations shown may be performed, for example, by a device (e.g., computing device 200), with the assistance of the device, and / or under the control of the device. In this regard, the execution of these operations may invoke one or more of the processor 202, memory 204, input / output circuitry 206, communication circuitry 208, image processing circuitry 210, and / or machine learning circuitry 212.

[0064] As shown in operations 405 and 410, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for comparing a detection limit and a limit threshold for each pixel. By way of example, computing device 200 may utilize one or more thresholds of the detection limit to compare the detection limit of each pixel with said one or more thresholds. The limit threshold may refer to, for example, any metric, specification, etc., that computing device 200 can use to determine whether the ability of imaging system 100 to quantify potential fugitive emissions 20 is increased or decreased. In some embodiments, satisfying the limit threshold at operations 405, 410 may mean that the detection limit value of a particular pixel exceeds a value associated with or defined by the limit threshold. This disclosure contemplates that in some embodiments, the limit threshold may be determined or assigned by a system administrator or user associated with imaging system 100. Additionally or alternatively, the limit threshold may be, for example, via... Figure 3 The iterative execution of the operation is determined by the imaging system 100.

[0065] When the detection limit satisfies the threshold, as shown in operation 415, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, and image processing circuitry 210 for assigning a first visual identifier to the corresponding pixel. By way of example, the first visual identifier may refer to a specific color, pattern, shape, etc., which, when viewed by a user, indicates to the user a group of pixels that have the specific pixel and other pixels with the first visual identifier. In other words, for each pixel with a detection limit that satisfies the threshold at operations 405 and 410, the first visual identifier may be the same (e.g., a common first color). When the detection limit fails to satisfy the threshold, as shown in operation 420, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, and image processing circuitry 210 for assigning a second visual identifier to the corresponding pixel. By way of example, the second visual identifier may refer to a specific color, pattern, shape, etc., which, when viewed by a user, indicates to the user a group of pixels that have the second visual identifier (e.g., and may be different from the first visual identifier). In other words, for each pixel that has a detection limit that fails to meet the limit threshold at operations 405 and 410, the second visual identifier can be the same (e.g., a common second color).

[0066] Subsequently, as shown in operation 425, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for rendering a detection limit map including a visual representation of each pixel based on visual identifiers assigned to the respective pixels, such as... Figure 5 An exemplary detection limit diagram is shown. By way of example, the imaging system 110 may include a display screen or otherwise communicatively coupled to a display screen, such that the computing device 200 can generate instructions for rendering a visual representation of each pixel in the pixels associated with the first IR image data using associated visual identifiers. Figure 5 As shown, for example, the first visual identifier 505 assigned to pixels having a detection limit that satisfies the threshold can be a first color or a first pattern. Similarly, as Figure 5 As shown, the second visual identifier 510 assigned to pixels with a detection limit that fails to meet the threshold can be a second color or a second pattern. Although described and illustrated with regard to two (e.g., first and second) visual identifiers, the present invention contemplates that the detection limit map can utilize any number of visual identifiers associated with the same pixel, pixel group, pixel subgroup, and / or the like, based on the intended application of the imaging system 100. Furthermore, this application contemplates that a user associated with the imaging system 100 can interact with the detection limit map, such as by selecting specific pixels or pixel groups for further analysis, consideration, etc. Figures 3 to 4 Iterative operations, etc.

[0067] In some embodiments, as shown in operation 430, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for modifying the detection limit map in response to iterative determination of thermal contrast and associated detection limits. Iteratively, as will be apparent from this disclosure, can be performed... Figure 3 The thermal contrast and detection limit are determined. For example, computing device 200 can iteratively receive probe temperature data and / or first IR image data, and iteratively determine or generate the thermal contrast of one or more pixels associated with the first IR image data, and then detect the associated detection limit based on these thermal contrast values. Therefore, Figure 4 The operation can also be performed iteratively to modify the detection limit diagram, thereby accurately reflecting any changes in the detection limit. In some implementations, Figure 3Subsequent execution of the operation may occur in response to a user request (e.g., a refresh request), which refreshes the detection limit map based on a subsequent comparison of the detection limit value with a limit threshold. For example, the user may specify a limit threshold that is important to the application of the imaging system, the user, etc., as described above. The computing device 200 may determine the minimum detection required for the path concentration as defined above, so that there is sufficient signal for the imaging device to generate an alarm in the presence of fugitive emissions. For example, a contrast ratio of 2-3 degrees Celsius may be used in some applications of the imaging system 100.

[0068] Figure 6 A flowchart illustrating a series of operations implemented on multiple devices is shown. As described above, Figure 5 The operations shown may be performed, for example, by a device (e.g., computing device 200), with the assistance of the device, and / or under the control of the device. In this regard, the execution of these operations may invoke one or more of the processor 202, memory 204, input / output circuitry 206, communication circuitry 208, image processing circuitry 210, and / or machine learning circuitry 212.

[0069] As shown in operation 605, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, and image processing circuitry 210 for receiving second IR image data associated with the field of view 105 of the second IR imaging device 104 from the second infrared (IR) imaging device 104. Similar to operation 305, the second IR image data generated by the second IR imaging device 104 may include multiple data entries, one or more of which may be associated with a specific pixel representing the FOV 105 of the second IR imaging device 104. Figure 1As shown, the second IR image data may include one or more data entries associated with or otherwise indicating the potential emission source 10. For example, the second IR image data may also indicate the intensity of IR radiation received by the second IR imaging device 104 for each pixel captured for the FOV 105. In embodiments where the computing device 200 and the second IR imaging device 104 are housed within a common or integrated device (e.g., the computing device 200 includes the second IR imaging device 104), the second IR image data may be received by the computing device 200 (e.g., internally transmitted, if any) as part of the normal operation of the second IR imaging device 104. In other embodiments where the computing device 200 and the second IR imaging device 104 are located separately (e.g., connected via network 106), the computing device 200 may be configured to receive the second IR image data from the second IR imaging device 104 in response to the generation of the second IR image data. In other words, each instance of the generated second IR image data may be transmitted to the computing device 200 at the time of generation. In other embodiments, computing device 200 may periodically (e.g., according to a defined rate or sampling protocol) request second IR image data from second IR imaging device 104.

[0070] As shown in operation 610, the apparatus (e.g., computing device 200) includes means such as processor 202, communication circuitry 208, image processing circuitry 210, etc., for determining background temperature data based on the second IR image data. As will be apparent from the relative positioning between the first IR imaging device 102 and the second IR imaging device 104, one or more pixels associated with the first IR image data can similarly be associated with the second IR image data. To provide additional data sources to improve the determination of thermal contrast and detection limits, system 100 may combine background image data based on the first IR image data with background temperature data based on the second IR image data. Thus, computing device 200 can be operated to refine the determination of thermal contrast and detection limits based on an increased dataset (e.g., a higher confidence output). Although described herein with reference to the second IR imaging device 104 and associated second IR image data, this disclosure contemplates the use of data input from various additional sources, including additional broadband IR image data, visual image data (e.g., VIS and / or RGB data), and / or similar data, to further improve upon the above references. Figures 3 to 4 and Figure 6 The aforementioned operations.

[0071] therefore, Figures 3 to 4 and Figure 6A flowchart illustrating the operation of an apparatus, method, and computer program product according to an exemplary embodiment contemplated herein is shown. It should be understood that each flowchart block, and combinations thereof, can be implemented by various means, such as hardware, firmware, processors, circuitry, and / or other devices associated with the execution of software including one or more computer program instructions. For example, one or more of the operations described above can be implemented by means of executing computer program instructions. In this regard, the computer program instructions can be stored in the memory 204 of computing device 200 and executed by the processor 202 of computing device 200.

[0072] It should be understood that any such computer program instructions can be loaded onto a computer or other programmable device (e.g., hardware) to produce a machine, such that the resulting computer or other programmable device performs the function specified in the flowchart block. These computer program instructions can also be stored in a computer-readable storage medium that instructs the computer or other programmable device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of writing, the execution of which performs the function specified in the flowchart block. The computer program instructions can also be loaded onto a computer or other programmable device to cause a series of operations to be performed on the computer or other programmable device, thereby producing a computer-implemented process, such that the instructions executing on the computer or other programmable device provide operations for performing the function specified in the flowchart block.

[0073] Flowchart blocks support combinations of devices for performing specified functions and combinations of operations for performing specified functions. It should be understood that one or more blocks in a flowchart, and combinations of blocks in a flowchart, can be implemented via computer instructions by a hardware-based dedicated computer system or a combination of dedicated hardware that performs the specified function.

Claims

1. An imaging system comprising: a first infrared (IR) imaging device configured to generate first IR image data of a field of view of the first IR imaging device; and a computing device operatively connected with the first IR imaging device, wherein the computing device is configured to: receive probe temperature data from a temperature probe communicably coupled with the computing device, wherein the probe temperature data is indicative of an external environment of the imaging system; receive the first IR image data from the first IR imaging device; determine background temperature data based on the first IR image data, wherein the background temperature data comprises a first temperature for each pixel among a plurality of pixels associated with the first IR image data; determine gas temperature data based on the probe temperature data, wherein the gas temperature data comprises a second temperature for each pixel among the plurality of pixels associated with the first IR image data; determine a thermal contrast for each pixel based on a comparison between the background temperature data and the gas temperature data; and determine a detection limit for each pixel as a function of the thermal contrast for each pixel and based on a radiative transfer model.

2. The imaging system of claim 1, wherein the temperature probe is located within the field of view of the first IR imaging device.

3. The imaging system of claim 1, wherein the imaging system includes the temperature probe and the temperature probe is attached to a housing that supports the first IR imaging device.

4. The imaging system of claim 1, further comprising a second IR imaging device configured to generate second IR image data of a field of view of the second IR imaging device and operatively connected with the computing device, wherein the computing device is further configured to determine the background temperature data based on the second IR image data.

5. A computer-implemented method comprising: receiving probe temperature data from a temperature probe, wherein the probe temperature data is indicative of an external environment of an imaging system; receiving first infrared (IR) image data of a field of view of a first IR imaging device from the first IR imaging device; determining background temperature data based on the first IR image data, wherein the background temperature data comprises a first temperature for each pixel among a plurality of pixels associated with the first IR image data; determining gas temperature data based on the probe temperature data, wherein the gas temperature data comprises a second temperature for each pixel among the plurality of pixels associated with the first IR image data; determining a thermal contrast for each pixel based on a comparison between the background temperature data and the gas temperature data; and determining a detection limit for each pixel as a function of the thermal contrast for each pixel and based on a radiative transfer model.

6. The computer-implemented method of claim 5, wherein the temperature probe is located within the field of view of the first IR imaging device. ​ ​ ​ 7. The computer-implemented method of claim 5, further comprising: receiving, from a second IR imaging device, second IR image data of a field of view of the second IR imaging device; and determining the background temperature data based on the second IR image data.

8. A computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon, the computer program code, when executed by at least one processor, configures the computer program product to: receive probe temperature data from a temperature probe, wherein the probe temperature data is indicative of an external environment of an imaging system; receive, from a first infrared (IR) imaging device, first IR image data of a field of view of the first IR imaging device; determine, based on the first IR image data, background temperature data, wherein the background temperature data comprises a first temperature for each pixel among a plurality of pixels associated with the first IR image data; determine, based on the probe temperature data, gas temperature data, wherein the gas temperature data comprises a second temperature for each pixel among the plurality of pixels associated with the first IR image data; determine, based on a comparison between the background temperature data and the gas temperature data, a thermal contrast for each pixel; and determine, from the thermal contrast for each pixel and based on a radiative transfer model, a detection limit for each pixel.

9. The computer program product of claim 8, further configured for: receiving, from a second IR imaging device, second IR image data of a field of view of the second IR imaging device; and determining the background temperature data based on the second IR image data.

10. The computer program product of claim 8, further configured for: comparing the detection limit for each pixel to a limit threshold; in the event that the detection limit satisfies the limit threshold, assigning a first visual identifier to the respective pixel; and in the event that the detection limit fails to satisfy the limit threshold, assigning a second visual identifier to the respective pixel.

Images