Infrared image data processing method and device and storage medium
The infrared image data collected by the infrared detector is processed with non-uniform correction and grayscale filtering through FPGA, and the background and detail layers are separated for adaptive filtering, which solves the problem of poor quality of infrared image data and improves image quality and observation capabilities.
Patent Information
- Application Number
- CN202510810592.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-17
- Publication Date
- 2025-09-23
AI Technical Summary
Infrared detectors are affected by the detection environment, resulting in poor quality of infrared image data. Especially when the target object is small or the temperature difference is small or large, the infrared image displayed on the display device has too high or too low contrast, low signal-to-noise ratio, and blurred edges and details.
A field programmable gate array (FPGA) is used to perform non-uniform correction and grayscale filtering on the original infrared image data collected by the infrared detector, and the background and detail layers are separated for adaptive filtering, including bilateral filtering, grayscale equalization, linear stretching and mean filtering, to improve image quality.
It improves the contrast of infrared images, enhances the edges of detailed textures, eliminates noise, improves the observation capability of faint target objects and the efficiency of effective information acquisition, and fully utilizes the parallel characteristics and high real-time computing capabilities of FPGA.
Smart Images
Figure CN120689254A_ABST
Abstract
Description
[0001] Technology Neighborhood
[0002] The present invention relates to the technical field of computer vision, and in particular to a method, device and storage medium for processing infrared image data. Background Art
[0003] Infrared detectors can obtain information such as surface thermal radiation and internal heat dissipation of objects, and provide thermal images of target objects and backgrounds, thus becoming a means for people to observe and perceive the objective world. They are widely used in security and other scenarios.
[0004] Infrared detectors use thermal radiation imaging and are greatly affected by external factors such as the temperature and humidity of the detection environment. When the target object to be observed is small, the local temperature difference of the target object is small, or the temperature difference between the target object and the observation environment is small or large, the infrared image data displayed by the display device will have excessively high or low contrast, low signal-to-noise ratio, blurred edges and details, etc., resulting in poor quality of the infrared image data. Summary of the Invention
[0005] In view of this, the present invention provides a method, device and storage medium for processing infrared image data, so as to improve the quality of infrared image data.
[0006] A first aspect of the present invention provides a method for processing infrared image data, which is applied to a field programmable gate array, wherein the field programmable gate array is connected to an infrared detector and a display device respectively, and the method comprises:
[0007] Receiving raw infrared image data collected by the infrared detector;
[0008] performing non-uniform correction on the original infrared image data to obtain candidate infrared image data;
[0009] performing grayscale filtering on the background and details of the candidate infrared image data respectively to obtain target infrared image data with enhanced details;
[0010] The target infrared image data is output to the display device for display.
[0011] A second aspect of the present invention provides an infrared image data processing device, which is applied to a field programmable gate array, wherein the field programmable gate array is connected to an infrared detector and a display device, respectively, and the device comprises:
[0012] An infrared image data receiving module, configured to receive the original infrared image data collected by the infrared detector;
[0013] a non-uniformity correction module, configured to perform non-uniformity correction on the original infrared image data to obtain candidate infrared image data;
[0014] a detail enhancement module, configured to perform grayscale filtering on the background and details of the candidate infrared image data to obtain detail-enhanced target infrared image data;
[0015] The infrared image data output module is used to output the target infrared image data to the display device for display.
[0016] A third aspect of the present invention provides an electronic device, comprising:
[0017] at least one processor; and
[0018] a memory communicatively connected to the at least one processor; wherein,
[0019] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can perform the infrared image data processing method as described in the first aspect above.
[0020] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for processing infrared image data as described in the first aspect above is implemented.
[0021] A fifth aspect of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the infrared image data processing method as described in the first aspect above.
[0022] In this embodiment, raw infrared image data captured by an infrared detector is received; non-uniformity correction is performed on the raw infrared image data to obtain candidate infrared image data; grayscale filtering is performed on the background and details of the candidate infrared image data to obtain detail-enhanced target infrared image data; and the target infrared image data is output to a display device for display. This embodiment distinguishes between background and detail layers in the infrared image data and performs adaptive grayscale filtering. The combination of these two layers improves contrast, enhances detail texture edges, and eliminates noise, effectively enhancing the quality of the infrared image data, enhancing the ability to observe faint targets, and improving the efficiency of acquiring effective information.
[0023] In addition, the detail enhancement function of infrared image data is implemented in FPGA, which has a high degree of integration, reduces PCB circuit redundancy, fully utilizes the parallel characteristics and high real-time computing capabilities of FPGA, and improves the processing efficiency of infrared image data.
[0024] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0026] Figure 1 This is a flowchart of a method for processing infrared image data provided by Example 1 of the present invention.
[0027] Figure 2 This is a system architecture diagram between an infrared detector, FPGA and a display device provided in Example 1 of the present invention.
[0028] Figure 3 This is an example diagram of original infrared image data provided by the first embodiment of the present invention.
[0029] Figure 4 This is an example diagram of candidate infrared image data provided by the first embodiment of the present invention.
[0030] Figure 5 This is a flowchart of detail enhancement provided by Example 1 of the present invention.
[0031] Figure 6 This is an example diagram of original image data of a background layer provided in the first embodiment of the present invention.
[0032] Figure 7 This is an example diagram of background layer filtered image data provided in Example 1 of the present invention.
[0033] Figure 8 This is an example diagram of a grayscale histogram of original image data of a background layer provided in the first embodiment of the present invention.
[0034] Figure 9 This is an example diagram of a grayscale histogram of background layer filtered image data provided in Example 1 of the present invention.
[0035] Figure 10 This is an example diagram of detail layer original image data provided in the first embodiment of the present invention.
[0036] Figure 11 This is an example diagram of detail layer filtered image data provided in Example 1 of the present invention.
[0037] Figure 12 This is an example diagram of a grayscale histogram of detail layer original image data provided in the first embodiment of the present invention.
[0038] Figure 13 This is an example diagram of a grayscale histogram of detail layer filtered image data provided in Example 1 of the present invention.
[0039] Figure 14 This is an example diagram of synthetic infrared image data provided by Example 1 of the present invention.
[0040] Figure 15 This is an example diagram of target infrared image data provided by the first embodiment of the present invention.
[0041] Figure 16 It is a structural diagram of an infrared image data processing device provided by the second embodiment of the present invention.
[0042] Figure 17 This is a structural diagram of an electronic device provided in Example 3 of the present invention. DETAILED DESCRIPTION
[0043] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.
[0044] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0045] Example 1
[0046] See also Figure 1, shows a flow chart of a method for processing infrared image data provided by the first embodiment of the present invention. The method can be executed by an infrared image data processing device. The infrared image data processing device can be implemented in the form of hardware and / or software. The infrared image data processing device can be configured in an electronic device. Figure 1 As shown, the method includes:
[0047] Step 101: Receive original infrared image data collected by an infrared detector.
[0048] The infrared image data processing method in this embodiment can be applied to a field programmable gate array (FPGA). FPGA is a programmable logic chip that can perform general functions, that is, it can be programmed to implement certain logic processing functions. In this embodiment, the FPGA is programmed to implement infrared image data processing functions (including non-uniformity correction, detail enhancement, etc.).
[0049] In practical applications, such as Figure 2 As shown, the field programmable gate array can be connected to the infrared detector and the display device respectively by wired or wireless means. For the method of processing infrared image data, the infrared detector is the input end and the display device is the output end.
[0050] Among them, infrared detectors are deployed in the factory's production workshop and other locations according to business requirements to collect infrared image data of target objects. Display equipment is deployed in the factory's monitoring room and other locations according to business requirements, and operation and maintenance personnel observe the target objects.
[0051] Furthermore, the infrared detector receives the thermal radiation of the observed object and the background, and generates an electrical signal corresponding to the thermal radiation through photoelectric conversion, such as Figure 3 The raw infrared image data is shown.
[0052] The FPGA is responsible for configuring relevant parameters of the infrared detector, such as gain, integration time, etc., and calibrating the infrared detector so that it can generate a stable electrical signal, thereby receiving the original infrared image data within the preset grayscale range collected by the infrared detector according to the configured parameters.
[0053] Step 102: Perform non-uniform correction on the original infrared image data to obtain candidate infrared image data.
[0054] like Figure 2 As shown, FPGA is responsible for performing non-uniform corrections such as two-point correction and single-point correction on the original infrared image data generated by the infrared detector, and the result is as follows Figure 4The candidate infrared image data shown suppresses non-uniform noise in patterns such as row stripes or column stripes caused by different response rates of infrared detector image sensors.
[0055] Step 103 : performing grayscale filtering on the background and details of the candidate infrared image data to obtain target infrared image data with enhanced details.
[0056] like Figure 2 As shown in the figure, the high real-time performance of FPGA is utilized to separate the candidate infrared image data into two layers: background and detail. The candidate infrared images are filtered separately, for example, contrast improvement, brightness adjustment, detail enhancement, noise suppression, grayscale compression, etc., and then the background and detail layers are superimposed to obtain the target infrared image data.
[0057] In one embodiment of the present invention, step 103 may include the following steps:
[0058] Step 1031: Perform bilateral filtering on the candidate infrared image data to obtain background layer original image data.
[0059] In this embodiment, if Figure 5 As shown, the candidate infrared image data can be processed by bilateral filtering to obtain the following Figure 6 The background layer original image data is shown.
[0060] Bilateral filtering is to add a sliding bilateral filtering window to the candidate image data and perform a combination of spatial domain weighted averaging and grayscale domain weighted averaging on the pixels in the neighborhood of the central pixel.
[0061] The weighted average in the spatial domain is a fixed value. Pixels closer to the neighborhood center receive higher weights, reducing the impact of distant pixels on filtering and thus smoothing the image through low-pass filtering. The weighted average in the grayscale domain varies with the grayscale difference within the neighborhood. Pixels with smaller grayscale differences from the center pixel receive higher weights, reducing the impact of pixels with larger grayscale variations and preventing over-filtering.
[0062] In the specific implementation, the bilateral filtering process is expressed as:
[0063]
[0064] Among them, f BF is the bilateral filtering function, (x, y) is the coordinate of the central pixel of the bilateral filtering window, (x', y') is the coordinate of the spatial neighborhood pixel of the bilateral filtering window, S x,yis the set of spatial neighborhood pixels of the bilateral filter window, f(x,y) is the pixel value of the center pixel of the bilateral filter window, f(x',y') is the pixel value of the spatial neighborhood pixel of the bilateral filter window, s is the standardized Gaussian function of the spatial domain, σ s is the standard deviation of the standardized Gaussian function in the spatial domain, g is the standardized Gaussian function in the frequency domain, σ g is the standard deviation of the standardized Gaussian function in the frequency domain, and exp is the natural exponential function.
[0065] Step 1032: Perform an equalization operation on the grayscale of the background layer original image data to obtain background layer filtered image data.
[0066] In this embodiment, if Figure 5 As shown, the grayscale equalization operation can be performed on the original image data of the background layer to obtain the following Figure 7 The background layer filtered image data is shown.
[0067] like Figure 8 As shown in FIG, after the original infrared image data collected by the infrared detector is processed with non-uniform correction and bilateral filtering, the grayscale distribution of the original image data of the background layer is more concentrated.
[0068] like Figure 9 As shown, the number of pixel distributions of each grayscale value in the original image data of the background layer can be calculated to obtain the grayscale distribution histogram of the original image data of the background layer. Based on the grayscale distribution histogram, the grayscale cumulative histogram is calculated to reflect the distribution of each grayscale level and all grayscale values below it, determine the grayscale range of histogram equalization, and map the grayscale cumulative histogram to the new grayscale level to obtain the background layer filtered image data, so that the grayscale distribution is more uniform.
[0069] In the specific implementation, to solve the problems of the original background image being concentrated in a similar grayscale range and the contrast being too low, the histogram equalization algorithm can be used to select a suitable grayscale range interval and evenly distribute the background layer filtered image in a larger grayscale interval. Then, the equalization operation is expressed as:
[0070]
[0071] Among them, w is the width of the original image of the background layer, h is the height of the original image of the background layer, and f (x) is the sum of the frequency values of the grayscale value in the original image of the background layer that is less than or equal to the threshold x, h max is the maximum grayscale value of the background layer filtered image, H (x) Grayscale value of the filtered image for the background layer.
[0072] For example, the grayscale range of the infrared detector is usually 0 to 16383, and the grayscale range of the display device is usually 0 to 255. In order to compress the grayscale of the background layer filtered image to the grayscale range of 0 to 255 to adapt to the display device, h max The value range is 0 to 255.
[0073] Step 1033: Subtract the background layer original image data from the candidate infrared image data to obtain the detail layer original image data.
[0074] In this embodiment, if Figure 5 As shown, the candidate infrared image data is subtracted from the background layer original image data to obtain Figure 10 The detail layer original image data shown here, the background layer and the detail layer are now separated so that corresponding image processing can be performed on these two parts of image data respectively.
[0075] Step 1034: linearly stretch the detail layer original image data in grayscale to obtain detail layer filtered image data.
[0076] In this embodiment, if Figure 5 As shown, the original image data of the detail layer can be linearly stretched in grayscale to obtain the following Figure 11 Detail layer filtered image data shown.
[0077] Since the original infrared image data collected by the infrared detector is subjected to non-uniform correction, the grayscale distribution of the candidate infrared image data and the original image of the background layer is relatively concentrated. Figure 12 As shown, the grayscale distribution histogram (ie, grayscale level) of the detail layer original image obtained by subtracting the two is smaller.
[0078] like Figure 13 As shown in the figure, in order to improve the edge clarity between the details and the surrounding background, the original image of the detail layer can be linearly stretched in grayscale, the maximum grayscale level and the minimum grayscale level of the original image of the detail layer can be compared, and the appropriate slope and intercept can be selected to map the grayscale distribution in a small range to a larger grayscale distribution range, expand the grayscale range of the details, increase the grayscale difference between the details and the surrounding background, and highlight the detail texture and edges.
[0079] In the specific implementation, linear stretching is expressed as:
[0080]
[0081] Among them, g min is the minimum grayscale value of the pixel in the original image of the detail layer, g max is the maximum grayscale value of the pixel in the original image of the detail layer, g' min is the minimum grayscale value of the pixel in the detail layer filtered image, g'max is the maximum grayscale value of the pixel in the expected detail layer filtered image, g (x) is the gray value of the pixel in the original image of the detail layer, G (x) is the grayscale value of the pixel in the detail layer filtered image.
[0082] Step 1035 : Perform a synthesis operation on the background layer filtered image data and the detail layer filtered image data to obtain synthesized infrared image data.
[0083] In this embodiment, the grayscale dynamic range of the background layer filtered image and the detail layer filtered image after filtering can be compressed to 0-255. Figure 5 As shown, the filtered background layer image and the detail layer image can be superimposed in a certain proportion to form a composite image as shown in Figure 14 The synthetic infrared image data shown can be superimposed at different ratios to achieve synthesis of different intensities.
[0084] In a specific implementation, the synthesis operation includes:
[0085] B (x) =]G (x) *a+H (x) *(16-a)]÷16
[0086] Among them, B (x) is the gray value of the pixel in the synthetic image data, G (x) is the grayscale value of the pixel in the detail layer filtered image, H (x) is the grayscale value of the pixel in the background layer filtered image, and a is the scale parameter of the detail layer filtered image.
[0087] Step 1036: Perform mean filtering on the synthesized infrared image data to obtain target infrared image data with enhanced details.
[0088] In this embodiment, the bilateral filtering process may have a weaker effect on suppressing salt and pepper noise. Figure 5 As shown, the mean filter is introduced to enhance the suppression of salt and pepper noise in the synthetic infrared image data, and the following is obtained: Figure 15 Detail-enhanced target infrared image data is shown.
[0089] In a specific implementation, the mean filtering process includes:
[0090]
[0091] Where (x, y) is the pixel point in the synthetic infrared image data, m(x, y) is the grayscale value of the pixel point in the synthetic infrared image data, S(ab) represents the filter window with a length of a and a width of b, and M (x,y) is the grayscale value of the pixel in the target infrared image data.
[0092] In this embodiment, detail enhancement involves algorithms such as grayscale equalization, grayscale linear stretching, image synthesis, and mean filtering. Users can adjust parameters according to the actual usage environment to achieve the best image effect, and the configuration is highly configurable.
[0093] Step 104: Output the target infrared image data to a display device for display.
[0094] In this embodiment, if Figure 2 As shown, the FPGA outputs the target infrared image data to the display device, and the display device is responsible for displaying the target infrared image data.
[0095] In this embodiment, raw infrared image data captured by an infrared detector is received; non-uniformity correction is performed on the raw infrared image data to obtain candidate infrared image data; grayscale filtering is performed on the background and details of the candidate infrared image data to obtain detail-enhanced target infrared image data; and the target infrared image data is output to a display device for display. This embodiment distinguishes between background and detail layers in the infrared image data and performs adaptive grayscale filtering. The combination of these two layers improves contrast, enhances detail texture edges, and eliminates noise, effectively enhancing the quality of the infrared image data, enhancing the ability to observe faint targets, and improving the efficiency of acquiring effective information.
[0096] In addition, the detail enhancement function of infrared image data is implemented in FPGA, which has a high degree of integration, reduces PCB circuit redundancy, fully utilizes the parallel characteristics and high real-time computing capabilities of FPGA, and improves the processing efficiency of infrared image data.
[0097] Example 2
[0098] See also Figure 16 , shows a schematic diagram of the structure of an infrared image data processing device provided by the second embodiment of the present invention. Applied to a field programmable gate array, the field programmable gate array is connected to an infrared detector and a display device, such as Figure 16 As shown, the device includes:
[0099] The infrared image data receiving module 1601 is used to receive the original infrared image data collected by the infrared detector;
[0100] A non-uniformity correction module 1602 is configured to perform non-uniformity correction on the original infrared image data to obtain candidate infrared image data;
[0101] A detail enhancement module 1603 is configured to perform grayscale filtering on the background and details of the candidate infrared image data to obtain detail-enhanced target infrared image data;
[0102] The infrared image data output module 1604 is configured to output the target infrared image data to the display device for display.
[0103] In one embodiment of the present invention, the detail enhancement module 1603 includes:
[0104] A bilateral filtering module, configured to perform bilateral filtering on the candidate infrared image data to obtain background layer original image data;
[0105] A grayscale equalization module is used to perform a grayscale equalization operation on the background layer original image data to obtain background layer filtered image data;
[0106] a detail image generating module, configured to subtract the background layer original image data from the candidate infrared image data to obtain detail layer original image data;
[0107] A grayscale linear stretching module, configured to linearly stretch the original image data of the detail layer in grayscale to obtain filtered image data of the detail layer;
[0108] an image synthesis module, configured to perform a synthesis operation on the background layer filtered image data and the detail layer filtered image data to obtain synthesized infrared image data;
[0109] The mean filtering module is used to perform mean filtering on the synthesized infrared image data to obtain target infrared image data with enhanced details.
[0110] In one embodiment of the present invention, the bilateral filtering process is expressed as:
[0111]
[0112] Among them, f BF is the bilateral filtering function, (x, y) is the coordinate of the central pixel of the bilateral filtering window, (x', y') is the coordinate of the spatial neighborhood pixel of the bilateral filtering window, S x,y is the set of spatial neighborhood pixels of the bilateral filter window, f(x,y) is the pixel value of the center pixel of the bilateral filter window, f(x',y') is the pixel value of the spatial neighborhood pixel of the bilateral filter window, s is the standardized Gaussian function of the spatial domain, σ s is the standard deviation of the standardized Gaussian function in the spatial domain, g is the standardized Gaussian function in the frequency domain, σ g is the standard deviation of the standardized Gaussian function in the frequency domain, and exp is the natural exponential function.
[0113] In one embodiment of the present invention, the balancing operation is expressed as:
[0114]
[0115] Wherein, w is the width of the original image of the background layer, h is the height of the original image of the background layer, and f (x) is the sum of the frequency values of the grayscale value in the original image of the background layer that is less than or equal to the threshold x, h max is the maximum grayscale value of the background layer filtered image, H (x) Grayscale value of the filtered image for the background layer.
[0116] In one embodiment of the present invention, the linear stretching is expressed as:
[0117]
[0118] Among them, g min is the minimum grayscale value of the pixel in the original image of the detail layer, g max is the maximum grayscale value of the pixel in the original image of the detail layer, g' min is the minimum grayscale value of the pixel in the detail layer filtered image, g' max is the maximum grayscale value of the pixel in the expected detail layer filtered image, g (x) is the grayscale value of the pixel in the original image of the detail layer, G (x) is the grayscale value of the pixel in the detail layer filtered image.
[0119] In one embodiment of the present invention, the synthesis operation includes:
[0120] B (x) =[G (x) *a+H (x) *(16-a)]÷16
[0121] Among them, B (x) is the gray value of the pixel in the synthetic image data, G (x) is the grayscale value of the pixel in the detail layer filtered image, H (x) is the grayscale value of the pixel in the background layer filtered image, and a is the scale parameter of the detail layer filtered image.
[0122] In one embodiment of the present invention, the mean filtering process includes:
[0123]
[0124] Wherein, (x, y) is the pixel point in the synthetic infrared image data, m(x, y) is the grayscale value of the pixel point in the synthetic infrared image data, S(ab) represents the filter window with a length of a and a width of b, and M (x,y) is the grayscale value of the pixel in the target infrared image data.
[0125] In one embodiment of the present invention, the infrared image data receiving module 1601 includes:
[0126] A parameter configuration module, used to configure parameters of the infrared detector;
[0127] The parameter receiving module is used to receive the original infrared image data collected by the infrared detector within a preset grayscale range according to the parameters.
[0128] The infrared image data processing device provided by the embodiment of the present invention can execute the infrared image data processing method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the infrared image data processing method.
[0129] Example 3
[0130] See also Figure 17 , which shows a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.
[0131] like Figure 17 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0132] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.
[0133] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the infrared image data processing method.
[0134] In some embodiments, the method for processing infrared image data can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for processing infrared image data described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for processing infrared image data in any other appropriate manner (e.g., by means of firmware).
[0135] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0136] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.
[0137] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0138] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
[0139] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.
[0140] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.
[0141] Example 4
[0142] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the infrared image data processing method provided by any embodiment of the present invention.
[0143] The computer program product may be implemented by writing computer program code for performing the operations of the present invention in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0144] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.
[0145] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.
Claims
1. A method for processing infrared image data, characterized in that: Applied to a field programmable gate array, the field programmable gate array is connected to an infrared detector and a display device respectively, and the method includes: Receiving raw infrared image data collected by the infrared detector; performing non-uniform correction on the original infrared image data to obtain candidate infrared image data; performing grayscale filtering on the background and details of the candidate infrared image data respectively to obtain target infrared image data with enhanced details; The target infrared image data is output to the display device for display.
2. The method according to claim 1, characterized in that The grayscale filtering process is performed on the background and details of the candidate infrared image data to obtain detail-enhanced target infrared image data, including: Performing bilateral filtering on the candidate infrared image data to obtain background layer original image data; Performing a grayscale equalization operation on the background layer original image data to obtain background layer filtered image data; Subtracting the background layer original image data from the candidate infrared image data to obtain detail layer original image data; linearly stretching the detail layer original image data in grayscale to obtain detail layer filtered image data; Performing a synthesis operation on the background layer filtered image data and the detail layer filtered image data to obtain synthesized infrared image data; Mean filtering is performed on the synthesized infrared image data to obtain target infrared image data with enhanced details.
3. The method according to claim 2, characterized in that The bilateral filtering process is expressed as: Among them, f BF is the bilateral filtering function, (x, y) is the coordinate of the central pixel of the bilateral filtering window, (x', y') is the coordinate of the spatial neighborhood pixel of the bilateral filtering window, S x,y is the set of spatial neighborhood pixels of the bilateral filter window, f(x,y) is the pixel value of the center pixel of the bilateral filter window, f(x',y') is the pixel value of the spatial neighborhood pixel of the bilateral filter window, s is the standardized Gaussian function of the spatial domain, σ s is the standard deviation of the standardized Gaussian function in the spatial domain, g is the standardized Gaussian function in the frequency domain, σ g is the standard deviation of the standardized Gaussian function in the frequency domain, and exp is the natural exponential function.
4. The method according to claim 2, characterized in that The balancing operation is expressed as: Wherein, w is the width of the original image of the background layer, h is the height of the original image of the background layer, and f (x) is the sum of the frequency values of the grayscale value in the original image of the background layer that is less than or equal to the threshold x, h max is the maximum grayscale value of the background layer filtered image, H (x) Grayscale value of the filtered image for the background layer.
5. The method according to claim 2, characterized in that The linear stretch is expressed as: Among them, g min is the minimum grayscale value of the pixel in the original image of the detail layer, g max is the maximum grayscale value of the pixel in the original image of the detail layer, g' min is the minimum grayscale value of the pixel in the detail layer filter image expectation, g' max is the maximum grayscale value of the pixel in the expected detail layer filtered image, g (x) is the grayscale value of the pixel in the original image of the detail layer, G (x) is the grayscale value of the pixel in the detail layer filtered image.
6. The method according to claim 2, characterized in that The synthesis operation includes: B (x) =[G (x) *a+H (x) *(16-a)]÷16 Among them, B (x) is the gray value of the pixel in the synthetic image data, G (x) is the grayscale value of the pixel in the detail layer filtered image, H (x) is the grayscale value of the pixel in the background layer filtered image, and a is the scale parameter of the detail layer filtered image.
7. The method according to claim 2, characterized in that The mean filtering process includes: Wherein, (x, y) is the pixel point in the synthetic infrared image data, m(x, y) is the grayscale value of the pixel point in the synthetic infrared image data, S(ab) represents the filter window with a length of a and a width of b, and M (x,y) is the grayscale value of the pixel in the target infrared image data.
8. The method according to any one of claims 1 to 7, characterized in that The receiving of the original infrared image data collected by the infrared detector includes: Configuring parameters for the infrared detector; The original infrared image data within a preset grayscale range collected by the infrared detector according to the parameters is received.
9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the infrared image data processing method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for processing infrared image data according to any one of claims 1 to 8 is implemented.