Thermal image processing method and apparatus for non-uniformity correction

Abstract

A thermal image processing method according to the present invention comprises the steps of: receiving a captured image from a thermal image camera; dividing each frame included in the captured image into a plurality of blocks; identifying each block as a target block or an excluded block on the basis of the pixel value difference between corresponding blocks of two neighboring frames and / or the average pixel value of each block of the frame; determining whether to mark each block position on the basis of the cumulative count of the target block within a plurality of frames; calculating a non-uniformity correction value for an unmarked block position; and outputting a corrected image by correcting the captured image on the basis of the calculated non-uniformity correction value.

Description

Thermal image processing method and apparatus for non-uniformity correction

[0001] The present invention relates to a thermal image processing method and apparatus for non-uniformity correction. Specifically, the present invention relates to a thermal image processing method and apparatus for non-uniformity correction that generates a corrected image by correcting the non-uniformity of a thermal image camera based on an image captured by a thermal image camera.

[0002]

[0003] The content described in this section merely provides background information regarding the present embodiment and does not constitute prior art.

[0004] Non-Uniformity Correction (NUC) is a technology primarily used in infrared (IR) and thermal imaging cameras. Each pixel in a sensor can react differently depending on temperature or other environmental factors, and these differences can cause distortion or noise in the image. NUC is the process of correcting such non-uniform responses to make the output image uniform.

[0005] NUC is a critical technology that corrects the non-uniform pixel response of infrared and thermal imaging cameras in various ways. Methods include pre-calibration through offline calibration or automatic real-time calibration based on environmental changes. Each calibration method is selected based on performance, cost, and the application environment, and plays a vital role in maintaining high-quality images.

[0006] This specification is a deliverable derived from the "Automotive Industry Technology Development (R&D)" project (Project Title: Development of ISP (Image Signal Processor) Semiconductor for XGA-Class Thermal Imaging Night Vision Cameras, Project No.: RS-2024-00405892) organized by the Korea Institute of Industrial Technology Planning and Evaluation under the Ministry of Trade, Industry and Energy.

[0007]

[0008] The objective of the present invention is to provide a thermal image processing method and apparatus for non-uniformity correction that corrects the non-uniformity of a captured image taken through a thermal imaging camera and generates a corrected image.

[0009] The objects of the present invention are not limited to those mentioned above, and other unmentioned objects and advantages of the present invention may be understood from the following description and will be more clearly understood by the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0010]

[0011] A thermal image processing method according to an embodiment of the present invention may include: receiving a captured image from a thermal imaging camera; dividing each frame included in the captured image into a plurality of blocks; classifying each block into a target block and an exclusion block based on at least one of the difference in pixel values ​​for corresponding blocks of two adjacent frames or the average pixel value of each block of the frame; determining whether to mark the location of each block based on the cumulative quantity of the target block within the plurality of frames; calculating a non-uniformity correction value for the location of the block that is not marked; and correcting the captured image based on the calculated non-uniformity correction value and outputting a corrected image.

[0012] Additionally, the step of dividing each of the above blocks into target blocks and exclusion blocks may include: a step of calculating the difference in pixel values ​​between corresponding pixels for a predetermined block of an adjacent first frame and a second frame; a step of calculating a block difference value by accumulating the difference in pixel values ​​for each pixel; and a step of dividing each block of the second frame into the target block or the exclusion block based on the block difference value.

[0013] In addition, the step of distinguishing between the target block or the exclusion block based on the block difference value may set the corresponding block of the second frame as the exclusion block when the block difference value exceeds a first threshold value.

[0014] Additionally, the step of dividing each of the above blocks into target blocks and exclusion blocks may include: a step of calculating the average pixel value of pixels included in a specific block of a specific frame; and a step of dividing the specific block into the target block or the exclusion block based on the difference between the pixel value of each pixel included in the specific block and the average pixel value of the specific block.

[0015] In addition, the step of distinguishing the specific block as the target block or the exclusion block may set the specific block as the exclusion block when the difference between the pixel value of a predetermined pixel and the average pixel value exceeds a second threshold.

[0016] Additionally, the step of determining whether to mark the block location may include, for each block location, a step of counting the cumulative quantity of the target block over a plurality of frames; and a step of adding a marking to the block location when the cumulative quantity of the block location exceeds a third threshold.

[0017] Additionally, the step of determining whether the block location is marked may further include, for each block location, a step of calculating the average pixel value of each pixel included in the block location using the target block accumulated during the plurality of frames; and a step of outputting the average pixel value of each pixel for the block location and whether the block location is marked.

[0018] Additionally, the step of calculating the non-uniformity correction value may include: a step of determining whether each of the block positions is marked; and, for the unmarked block positions, a step of calculating a pixel-by-pixel non-uniformity correction value of the block position based on the average pixel value of each pixel included in the block position.

[0019] Additionally, the step of calculating the pixel-by-pixel non-uniformity correction value may include: a step of calculating the block average pixel value of the block location based on the average pixel value of each pixel; and a step of calculating the pixel-by-pixel non-uniformity correction value of the block location based on the difference between the average pixel value of each pixel included in the block location and the block average pixel value of the block location.

[0020] In addition, a thermal image processing device according to an embodiment of the present invention comprises: a memory storing a thermal image processing program; and a processor for executing the thermal image processing program, wherein the thermal image processing program may include: receiving a captured image from a thermal image camera; dividing each frame included in the captured image into a plurality of blocks; classifying each block into a target block and an exclusion block based on at least one of the difference in pixel values ​​for corresponding blocks of two adjacent frames or the average pixel value of each block of the frame; determining whether to mark the position of each block based on the cumulative quantity of the target blocks within the plurality of frames; and calculating a non-uniformity correction value for the target blocks that are not marked.

[0021] Additionally, in the thermal image processing program, the step of dividing each block into a target block and an exclusion block may include: a step of calculating the difference in pixel values ​​between corresponding pixels for a predetermined block of an adjacent first frame and a second frame; a step of calculating a block difference value by accumulating the difference in pixel values ​​for each pixel; and a step of dividing each block of the second frame into the target block or the exclusion block based on the block difference value.

[0022] Additionally, in the thermal image processing program, the step of dividing each block into a target block and an exclusion block may include: a step of calculating the average pixel value of pixels included in a specific block of a specific frame; and a step of dividing the specific block into the target block or the exclusion block based on the difference between the pixel value of each pixel included in the specific block and the average pixel value of the specific block.

[0023] Additionally, in the thermal image processing program, the step of determining whether to mark the block location may include, for each block location, a step of counting the cumulative quantity of the target block over a plurality of frames; and a step of adding a marking to the specific block location when the cumulative quantity of the specific block location exceeds a third threshold.

[0024] Additionally, in the thermal image processing program, the step of calculating the non-uniformity correction value may include: a step of determining whether each of the block locations is marked; and a step of calculating a pixel-by-pixel non-uniformity correction value for the block locations based on the average pixel value of each pixel included in the block locations for the unmarked block locations.

[0025]

[0026] The thermal image processing method and apparatus for non-uniformity correction according to the present invention determines the non-uniformity of the thermal image camera based on an actual captured image, so that non-uniformity can be reflected in real time.

[0027] In addition, the thermal image processing method and apparatus for non-uniformity correction according to the present invention can increase the accuracy of non-uniformity correction by calculating non-uniformity correction values ​​for each block.

[0028] In addition to the above, the specific effects of the present invention are described together with the specific details for implementing the invention below.

[0029]

[0030] FIGS. 1 to 4 are conceptual diagrams schematically illustrating a thermal imaging processing system including a thermal imaging processing device according to an embodiment of the present invention.

[0031] FIGS. 5 to 7 are exemplary diagrams for explaining the operation of a thermal image processing device.

[0032] FIG. 8 is a flowchart illustrating a thermal image processing method according to an embodiment of the present invention.

[0033] FIG. 9 is a flowchart for explaining the process of classifying each block into a target block or an exclusion block based on the first condition shown in FIG. 8.

[0034] FIG. 10 is a flowchart for explaining the process of classifying each block into a target block or an exclusion block based on the second condition shown in FIG. 8.

[0035] FIG. 11 is a flowchart for explaining the process of determining whether to mark the block location shown in FIG. 8.

[0036] FIG. 12 is a flowchart illustrating the process of calculating non-uniformity correction values ​​for unmarked block locations shown in FIG. 8.

[0037]

[0038] Terms and words used in this specification and claims shall not be interpreted as being limited to their general or dictionary meanings. In accordance with the principle that an inventor may define the concept of a term or word to best describe their invention, they shall be interpreted in a meaning and concept consistent with the technical spirit of the invention. Furthermore, since the embodiments described in this specification and the configurations illustrated in the drawings are merely one embodiment of the invention and do not represent the entire technical spirit of the invention, it should be understood that various equivalents, modifications, and applicable examples capable of replacing them may exist at the time of filing this application.

[0039] The terms first, second, A, B, etc., as used in this specification and claims may be used to describe various components, but said components should not be limited by said terms. These terms are used solely for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component. The term "and / or" includes a combination of a plurality of related described items or any of a plurality of related described items.

[0040] The terms used in this specification and claims are used merely to describe specific embodiments and are not intended to limit the invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as "comprising" or "having" should be understood as not precluding the existence or addition of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification.

[0041] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which this invention pertains.

[0042] Terms such as those defined in commonly used dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0043] In addition, each component, process, procedure, or method included in each embodiment of the present invention may be shared within a scope that is not technically contradictory to one another.

[0044] Hereinafter, with reference to FIGS. 1 to 14, a thermal image processing apparatus and method according to embodiments of the present invention will be described in detail.

[0045]

[0046] First, a thermal imaging processing device will be described with reference to FIGS. 1 to 4.

[0047] FIGS. 1 to 4 are conceptual diagrams schematically illustrating a thermal imaging processing system to which the thermal imaging processing device of the present invention is applied. FIGS. 5 to 7 are exemplary diagrams for explaining the operation of the thermal imaging processing device.

[0048] A thermal image processing system (1001, 1002, 1003, 1004) includes a thermal image camera (100) and a thermal image processing device (200), and the thermal image processing device (200) receives a captured image from the thermal image camera (100), determines whether non-uniformity occurs based on the captured image, corrects the non-uniformity, and outputs a corrected image.

[0049] The first thermal image processing system (1001) according to the first embodiment shown in FIG. 1 and the second thermal image processing system (1002) according to the second embodiment shown in FIG. 2 represent a structure in which a thermal image camera (100) and a thermal image processing device (200) are provided as separate devices.

[0050] The first thermal image processing system (1001) and the second thermal image processing system (1002) receive a captured image taken by a thermal image processing device (200) through a thermal image camera (100), determine whether non-uniformity occurs in the thermal image camera (100) based on the captured image, generate a non-uniformity correction value according to the determination result, and output a corrected image in which the captured image is corrected using the non-uniformity correction value.

[0051] At this time, the thermal image processing device (200) can generate a correction image for both the image captured by the thermal image camera (100) including a shutter as in FIG. 1 and the image captured by the thermal image camera (100) not including a shutter as in FIG. 2.

[0052] In addition, the third thermal image processing system (1003) according to the third embodiment shown in FIG. 3 and the fourth thermal image processing system (1004) according to the fourth embodiment shown in FIG. 4 represent a structure in which a thermal image camera (100) and a thermal image processing device (200) are configured as a single device.

[0053] The third thermal image processing system (1003) and the fourth thermal image processing system (1004) can omit the process of converting the measured values ​​of the thermal image sensor into images and directly correct the non-uniformity of each pixel of the thermal image sensor to output a corrected image. At this time, the third thermal image processing system (1003) may be provided with a structure including a shutter, and the fourth thermal image processing system (1004) may be provided with a structure not including a shutter.

[0054] Next, a thermal image processing device (200) will be described with reference to FIG. 1.

[0055] The thermal image processing device (200) may include an input interface, memory, a processor, and an output interface. The input interface receives a captured image from a thermal image camera (100). The memory stores a thermal image processing program, and the processor can generate a corrected image by executing the thermal image processing program stored in the memory. The output interface can output the corrected image generated by the thermal image processing program.

[0056]

[0057] Referring to FIGS. 5 to 7, the operation of the thermal image processing program is described in detail. The thermal image processing program receives a captured image including a plurality of frames (F) as in FIG. 5 from a thermal image camera (100), and divides each frame (F) included in the captured image into a plurality of blocks (B) as in FIG. 6.

[0058] Then, based on the distinction condition, each block (B) is divided into target blocks and exclusion blocks, and a decision is made on whether to mark each block location based on the cumulative number of target blocks for each block location within a plurality of frames included in the captured video.

[0059] Subsequently, a non-uniformity correction value for the corresponding block location is calculated using the accumulated target block for the unmarked block location, and a corrected image is output by correcting the captured image based on the calculated non-uniformity correction value.

[0060] Next, each operation of the thermal image processing program will be explained in detail.

[0061] First, the operation of a thermal image processing program classifying each block into target blocks and exclusion blocks based on a classification condition is described. At this time, the classification condition may include a first condition based on the difference in pixel values ​​for corresponding blocks of two adjacent frames and a second condition based on the average pixel value of each block of a frame.

[0062] To explain the operation of distinguishing each block into a target block and an exclusion block according to a first condition based on the difference in pixel values ​​for corresponding blocks of two adjacent frames, the thermal image processing program calculates the difference in pixel values ​​between corresponding pixels (P) for a predetermined block (B) of two adjacent frames in a plurality of frames (F) of a captured image, and calculates a block difference value by accumulating the difference in pixel values ​​for each pixel (P).

[0063] And, if the block difference value exceeds the first threshold, the corresponding block (B) of the second frame (F2) is set as an exclusion block, and otherwise, the corresponding block (B) is set as a target block.

[0064] The operation of setting the first block (B11) of the first frame (F1) and the second frame (F2) as a target block or an exclusion block is explained as an example. The first pixel (P) of the first block (B11) of the first frame (F1) 1_1 ) and the first pixel (P) of the first block (B11) of the second frame (F2). 2_1 Calculate the difference in pixel values ​​of ), and the second pixel (P) of the first block (B11) of the first frame (F1). 1_2 ) and the second pixel (P) of the first block (B11) of the second frame (F2). 2_2 Calculate the difference in pixel values ​​of ), and perform this process for all pixels (P).

[0065] And, through mathematical formula 1, the block difference value (F t Calculate ) and block difference value (F t If ) exceeds the first threshold, the first block (B11) of the second frame (F2) is set as an exclusion block, and otherwise, the first block (B11) of the second frame (F2) is set as a target block.

[0066]

[0067] [Mathematical Formula 1]

[0068]

[0069]

[0070] Next, an operation to distinguish each block into target blocks and exclusion blocks based on a second condition based on the average pixel value of each block of the frame is described.

[0071] The thermal image processing program calculates the average pixel value of the pixels (P) included in each block of the frame (F), and if the difference between the pixel value of each pixel (P) included in the block and the average pixel value of the block exceeds a second threshold, the block is set as an exclusion block, otherwise, the block is set as a target block.

[0072] The process of setting the first block (B11) of the first frame (F1) as a target block or an exclusion block is explained as an example. The first pixel (P) of the first block (B11) of the first frame (F1). 1-1 From ) the nth pixel (P 1-n Calculate the average pixel value of the first block (B11) using the pixel value of each pixel (P) up to ).

[0073] And, through mathematical formula 2, the first pixel (P 1_1 From ) the nth pixel (P 1_n Calculate the pixel value difference (Diff_pixel(x)) between each pixel's pixel value (x) and the average pixel value (Average(Block)) of the first block (B11), and if there is at least one pixel (P) where the pixel value difference (Diff_pixel(x)) exceeds the second threshold, set the first block (B11) as an exclusion block.

[0074]

[0075] [Mathematical Formula 2]

[0076]

[0077]

[0078] A thermal image processing program can classify each block of a frame into a target block or an exclusion block based on at least one of the first and second conditions described above.

[0079] Next, the operation of marking each block location based on the cumulative quantity of target blocks within multiple frames is described.

[0080] The thermal imaging processing program measures the cumulative quantity of target blocks for each block location across multiple frames. Then, if the cumulative quantity of target blocks does not exceed a third threshold, a marking is added to the corresponding block location; otherwise, a marking is added to the corresponding block location.

[0081] Subsequently, the thermal image processing program calculates the pixel-by-pixel average value using the accumulated target blocks and outputs the pixel-by-pixel average value and marking status for each block location. At this time, the third threshold value for the accumulated quantity for each block location may be set identically for all block locations or may be set differently for each block location.

[0082] Finally, the operation of a thermal imaging processing program to calculate non-uniformity correction values ​​for unmarked block locations is described.

[0083] The thermal imaging processing program determines whether each block location is marked and can calculate a pixel-by-pixel non-uniformity correction value for each block location based on the pixel-by-pixel average value of the target block accumulated at unmarked block locations. More specifically, the thermal imaging processing program calculates the block average pixel value for a corresponding block location using the pixel-by-pixel average value of the block location, calculates a non-uniformity correction value for each pixel based on the difference between the pixel average value and the block average pixel value, and thereby calculates the pixel-by-pixel non-uniformity correction value for the corresponding block location.

[0084]

[0085] FIG. 8 is a flowchart illustrating a thermal image processing method according to an embodiment of the present invention. FIG. 9 is a flowchart illustrating a process of classifying each block into a target block or an exclusion block based on a first condition illustrated in FIG. 8. FIG. 10 is a flowchart illustrating a process of classifying each block into a target block or an exclusion block based on a second condition illustrated in FIG. 8. FIG. 11 is a flowchart illustrating a process of determining whether to mark a block location illustrated in FIG. 8. FIG. 12 is a flowchart illustrating a process of calculating a non-uniformity correction value for an unmarked block location illustrated in FIG. 8.

[0086] Referring to FIGS. 1 and FIGS. 8, a thermal image processing method using a thermal image processing device (200) is described. The thermal image processing method receives a captured image including a plurality of frames (F) as in FIG. 5 from a thermal image camera (100) (step S110), and divides each frame (F) included in the captured image into a plurality of blocks (B) as in FIG. 6 (step S120).

[0087] Then, based on the distinction condition, each block (B) is divided into target blocks and exclusion blocks (step S130, step S140), and a decision is made on whether to mark each block location based on the cumulative number of target blocks for each block location within a plurality of frames included in the captured video (step S150).

[0088] Afterwards, a non-uniformity correction value for the corresponding block location can be calculated using the accumulated target block for the unmarked block location (step S160), and a corrected image can be output by correcting the captured image based on the calculated non-uniformity correction value (step S170).

[0089] Next, each step is explained in detail.

[0090] First, the process of a thermal image processing program dividing each block into a target block and an exclusion block based on a distinction condition (steps S130, S140) is described. At this time, the distinction condition may include a first condition based on the difference in pixel values ​​for corresponding blocks of two adjacent frames and a second condition based on the average pixel value of each block of a frame.

[0091] Referring to FIG. 9, a process (step S130) of dividing each block into a target block and an exclusion block according to a first condition based on the difference in pixel values ​​for corresponding blocks of two adjacent frames is described. The thermal image processing device (200) calculates the difference in pixel values ​​between corresponding pixels (P) for a predetermined block (B) of two adjacent frames in a plurality of frames (F) of a captured image (step S131), and calculates a block difference value (step S132) by accumulating the difference in pixel values ​​for each pixel (P).

[0092] Then, it is determined whether the block difference value exceeds the first threshold value (step S133), and if the block difference value exceeds the first threshold value, the corresponding block (B) of the second frame (F2) is set as an excluded block (step S134), and if not, the corresponding block (B) of the second frame (F2) is set as a target block (step S135).

[0093] Referring to FIGS. 5 to 7, an operation to set the first block (B11) of the first frame (F1) and the second frame (F2) as a target block or an exclusion block is described by example. The first pixel (P) of the first block (B11) of the first frame (F1) 1_1 ) and the first pixel (P) of the first block (B11) of the second frame (F2). 2_1 Calculate the difference in pixel values ​​of ), and the second pixel (P) of the first block (B11) of the first frame (F1). 1_2 ) and the second pixel (P) of the first block (B11) of the second frame (F2). 2_2Calculate the difference in pixel values ​​of ), and perform this process for all pixels (P).

[0094] And, through mathematical formula 1, the block difference value (F t Calculate ) and block difference value (F t If ) exceeds the first threshold, the first block (B11) of the second frame (F2) is set as an exclusion block, and otherwise, the first block (B11) of the second frame (F2) is set as a target block.

[0095]

[0096] [Mathematical Formula 1]

[0097]

[0098]

[0099] Next, referring to FIG. 10, a process (step S140) of dividing each block into a target block and an exclusion block according to a second condition based on the average pixel value of each block of the frame is described.

[0100] For each frame (F), the thermal image processing device (200) calculates the average pixel value of the pixels (P) included in each block (step S141) and calculates the difference between the pixel value of each pixel (P) included in each block and the average pixel value of each block (step S142). Then, it determines whether the difference value exceeds a second threshold value (step S143), and if the difference value of the pixels exceeds the second threshold value, it sets the corresponding block as an exclusion block (step S144).

[0101] On the other hand, if the difference value of a pixel does not exceed the second threshold, it is determined whether step S143 has been performed for all pixels, that is, whether the difference value for all pixels has been compared with the second threshold (step S145); if step S143 has been performed for all pixels, the corresponding block is set as the target block (step S146); otherwise, step S142 can be performed for other pixels.

[0102] To explain the process of setting the first block (B11) of the first frame (F1) as a target block or an exclusion block, for example, regarding the first block (B11) of the first frame (F1), the first pixel (P 1-1 From ) the nth pixel (P 1-n Calculate the average pixel value of the first block (B11) for each pixel (P) up to ).

[0103] And, through mathematical formula 2, the first pixel (P 1_1 From ) the nth pixel (P 1_n Calculate the pixel value difference (Diff_pixel(x)) between each pixel's pixel value (x) and the average pixel value (Average(Block)) of the first block (B11), and if there is at least one pixel (P) where the pixel value difference (Diff_pixel(x)) exceeds the second threshold, set the first block (B11) as an exclusion block.

[0104]

[0105] [Mathematical Formula 2]

[0106]

[0107]

[0108] The thermal image processing device (200) can classify each block of the frame into a target block or an exclusion block based on at least one of step S130 and step S140.

[0109] Next, referring to FIG. 11, a process (step S150) of marking each block based on the cumulative quantity of target blocks within a plurality of frames is described.

[0110] The thermal image processing device (200) counts the accumulated quantity of target blocks for the same location in a plurality of frames (step S151). Then, it determines whether the accumulated quantity of target blocks exceeds a third threshold (step S152), and if the accumulated quantity exceeds the third threshold, it calculates the pixel-by-pixel average value for the accumulated target blocks using the accumulated target blocks (step S153). On the other hand, if the accumulated quantity does not exceed the third threshold, it adds a marking to the location of the corresponding block (step S154). Subsequently, for each block location, it outputs the pixel-by-pixel average value and whether a marking is present (step S155).

[0111] Finally, the process (S160) of calculating a non-uniformity correction value for each block position is explained with reference to FIG. 12.

[0112] The thermal imaging processing device (200) determines whether a block location is marked (step S161), and if the block location is not marked, calculates the block average pixel value based on the pixel-by-pixel average pixel value (step S162). Then, it calculates the pixel-by-pixel non-uniformity correction value of the corresponding block based on the difference between the pixel average pixel value of each pixel and the block average pixel value (step S163), and stores the calculated non-uniformity correction value (step S164). On the other hand, if the block location is marked in step S161, the process of calculating the non-uniformity correction value for the corresponding block may be omitted.

[0113] Next, to explain the process of correcting the captured image based on the non-uniformity correction value and outputting the corrected image (step S170), the thermal image processing device (200) updates the non-uniformity correction value currently set at the corresponding block location with the non-uniformity correction value calculated in the process of calculating the non-uniformity correction value (step S160), and can correct the captured image based on the non-uniformity correction value set for each block location to generate the corrected image.

[0114]

[0115] The above description is merely an illustrative explanation of the technical concept of the present embodiment, and a person skilled in the art to which the present embodiment belongs would be able to make various modifications and variations within the scope of the essential characteristics of the present embodiment. Accordingly, the present embodiments are intended to explain, not limit, the technical concept of the present embodiment, and the scope of the technical concept of the present embodiment is not limited by these embodiments. The scope of protection of the present embodiment shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of the present embodiment.

[0116]

[0117] [Explanation of the symbol]

[0118] 1001, 1002, 1003, 1004: Thermal imaging processing system

[0119] 100: Thermal imaging camera

[0120] 200: Thermal imaging processing device

Claims

1. A thermal image processing method for correcting images captured by a thermal imaging camera, A step of receiving a captured image from a thermal imaging camera; A step of dividing each frame included in the above-mentioned captured image into a plurality of blocks; A step of dividing each block into a target block and an exclusion block based on at least one of the difference in pixel values ​​for corresponding blocks of two adjacent frames or the average pixel value of each block of said frame; A step of determining whether to mark each block position based on the cumulative quantity of the target blocks within a plurality of frames; A step of calculating a non-uniformity correction value for the above unmarked block location; and A step of correcting the captured image based on the calculated non-uniformity correction value and outputting a corrected image. Thermal imaging processing method.

2. In Paragraph 1, The step of dividing each of the above blocks into target blocks and exclusion blocks is: For a predetermined block of adjacent first and second frames, a step of calculating the difference in pixel values ​​between corresponding pixels; A step of calculating a block difference value by accumulating the pixel value difference for each pixel; and A thermal image processing method comprising the step of classifying each block of the second frame into the target block or the exclusion block based on the block difference value.

3. In Paragraph 2, The step of classifying into the target block or the exclusion block based on the block difference value is: A thermal image processing method that sets the corresponding block of the second frame as the exclusion block when the block difference value exceeds a first threshold value.

4. In Paragraph 1, The step of dividing each of the above blocks into target blocks and exclusion blocks is: A step of calculating the average pixel value of pixels included in a specific block of a specific frame; and A thermal image processing method comprising the step of classifying a specific block into a target block or an exclusion block based on the difference between the pixel value of each pixel included in the specific block and the average pixel value of the specific block.

5. In Paragraph 4, The step of classifying the above specific block into the above target block or the above exclusion block is, A thermal image processing method that sets a specific block as an exclusion block when the difference between the pixel value of a predetermined pixel and the average pixel value exceeds a second threshold.

6. In Paragraph 1, The step of determining whether to mark the above block location is, For each block location, a step of counting the cumulative quantity of the target block over a plurality of frames; and A thermal image processing method comprising the step of adding a marking to the block location when the accumulated quantity of the block location exceeds a third threshold.

7. In Paragraph 6, The step of determining whether to mark the above block location is, For each block location, a step of calculating the average pixel value of each pixel included in the corresponding block location using the target block accumulated during the plurality of frames; and A thermal image processing method further comprising the step of outputting the average pixel value of each pixel for the above block location and whether the above block location is marked.

8. In Paragraph 1, The step of calculating the above non-uniformity correction value is, A step of determining whether to mark each of the above block positions; and A thermal image processing method comprising the step of calculating a pixel-by-pixel non-uniformity correction value for the block location based on the average pixel value of each pixel included in the block location, for the unmarked block location.

9. In Paragraph 8, The step of calculating the above-mentioned pixel-by-pixel non-uniformity correction value is A step of calculating the block average pixel value of the block location based on the average pixel value of each of the above pixels; and A thermal image processing method for calculating a pixel-by-pixel non-uniformity correction value of a block location based on the difference between the average pixel value of each pixel included in the block location and the block average pixel value of the block location.

10. A thermal image processing device for correcting images captured by a thermal imaging camera, Memory where a thermal imaging processing program is stored; and It includes a processor that executes the above thermal image processing program, The above thermal imaging processing program is, A step of receiving a captured image from a thermal imaging camera; A step of dividing each frame included in the above-mentioned captured image into a plurality of blocks; A step of dividing each block into a target block and an exclusion block based on at least one of the difference in pixel values ​​for corresponding blocks of two adjacent frames or the average pixel value of each block of said frame; A step of determining whether to mark a block location based on the cumulative quantity of the target block within a plurality of frames; and A step comprising calculating a non-uniformity correction value for the above unmarked block location Thermal imaging processing device.

11. In Paragraph 10, In the above thermal image processing program, The step of dividing each of the above blocks into target blocks and exclusion blocks is: For a predetermined block of adjacent first and second frames, a step of calculating the difference in pixel values ​​between corresponding pixels; A step of calculating a block difference value by accumulating the pixel value difference for each pixel; and A thermal image processing device comprising the step of classifying each block of the second frame into the target block or the exclusion block based on the block difference value.

12. In Paragraph 10, In the above thermal image processing program, The step of dividing each of the above blocks into target blocks and exclusion blocks is: A step of calculating the average pixel value of pixels included in a specific block of a specific frame; and A thermal image processing device comprising the step of classifying a specific block into a target block or an exclusion block based on the difference between the pixel value of each pixel included in the specific block and the average pixel value of the specific block.

13. In Paragraph 10, In the above thermal image processing program, The step of determining whether to mark the above block location is, For each block location, a step of counting the cumulative quantity of the target block over a plurality of frames; and A thermal image processing device comprising the step of adding a marking to a specific block location when the accumulated quantity of a specific block location exceeds a third threshold.

14. In Paragraph 10, In the above thermal image processing program, The step of calculating the above non-uniformity correction value is, A step of determining whether to mark the position of each block; and A thermal image processing device comprising the step of calculating a pixel-by-pixel non-uniformity correction value for the block location based on the average pixel value of each pixel included in the block location for the unmarked block location.

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