Infrared image dimming method and system

Abstract

The invention provides a dimming method and system for an infrared image. The dimming method comprises the following steps: determining a dynamic range Vr, a gray minimum value Vmin and a gray maximum value Vmax of the infrared image; determining a pixel segmentation threshold value V [sigma] and a brightness threshold value D [sigma]; and in the infrared image, pixel points in the range of [Vmin, Vsigma] are mapped to a gray scale range smaller than a brightness threshold value D sigma, and pixel points in the range of [Vsigma, Vmax] are mapped to a gray scale range larger than or equal to the brightness threshold value D sigma, so that a brightness mapping image X is obtained. According to the invention, pixel points in different ranges in the infrared image can be mapped to different gray scale ranges based on the pixel segmentation threshold value V sigma and the brightness threshold value D sigma, so that a large-area high-temperature area, a small-area high-temperature area and a high-temperature area slightly higher than the environment temperature can be fully highlighted in the dimming image.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method and system for dimming infrared images. Background Technology

[0002] In the use of infrared imaging equipment (such as infrared thermal imagers), it is usually necessary to adjust the infrared images (such as...) according to the actual imaging effect and task requirements. Figure 1 The image is processed to highlight high-temperature areas (as shown in section (a)) by adjusting the brightness. Figure 1 (as shown in section (b)).

[0003] Currently, users mostly highlight areas with temperatures greater than or equal to the temperature threshold by manually setting the threshold. This process can be accomplished based on methods such as static threshold segmentation and color mapping, but it has the following drawbacks:

[0004] 1. Users need to manually set or modify the temperature threshold for high temperature protrusion according to different usage environments. This process depends on the user's operating experience. If the user's actual operating experience is insufficient, the dimming effect will not meet expectations. Furthermore, the user will need to repeatedly modify the temperature threshold, resulting in a poor user experience.

[0005] 2. Use red to highlight high-temperature areas (e.g., Figure 1 (as shown in part (b)), but this will reduce the contrast of the area, further causing the target details in the high-temperature area to be lost and the target features to be unable to be highlighted;

[0006] 3. For example Figure 1 As shown in section (b), only large areas of high temperature can be highlighted, and it cannot highlight areas such as... Figure 1 The small high-temperature areas shown in part (a) and the high-temperature areas that are slightly higher than the ambient temperature, such as areas that are 1°C-5°C higher than the ambient temperature, are due to the fact that the small high-temperature areas have too little weight, resulting in insufficient overall contrast after dimming. Their brightness is close to that of the background image, making them not prominent. When the temperature of the high-temperature area is slightly higher than the ambient temperature, the contrast of the high-temperature area is also not high after dimming because the two temperatures are close, thus failing to fully highlight the high-temperature areas that are slightly higher than the ambient temperature. Summary of the Invention

[0007] The purpose of this invention is to provide a method and system for dimming infrared images, which can be based on pixel segmentation threshold V. σ and brightness threshold D σ By mapping pixels in different ranges of infrared images to different grayscale ranges, large high-temperature areas, small high-temperature areas, and high-temperature areas slightly higher than the ambient temperature can all be fully highlighted in the dimmed image.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] On the one hand, a method for dimming infrared images is provided, characterized by comprising the following steps:

[0010] Determine the dynamic range V of the infrared image r Minimum grayscale value V min Maximum grayscale value V max ;

[0011] Determine the pixel segmentation threshold V σ and brightness threshold D σ ;

[0012] In the infrared image, [V min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V max Pixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, a brightness-mapped image X is obtained.

[0013] On the other hand, an infrared image dimming system is also provided, characterized in that it includes:

[0014] The grayscale statistics module is used to determine the number of samples n(V) for each grayscale value in the infrared image, and to obtain the dynamic range V of the infrared image. r Minimum grayscale value V min Maximum grayscale value V max ;

[0015] The threshold setting module is used to determine the pixel segmentation threshold V. σ and brightness threshold D σ ,

[0016] And, a mapping module, which is used to map [V] from the infrared image. min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V max Pixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, a brightness-mapped image X is obtained.

[0017] In summary, the present invention has the following advantages compared with the prior art:

[0018] This invention can be based on pixel segmentation threshold V σ and brightness threshold Dσ This process maps pixels in different ranges of an infrared image to different grayscale ranges. It achieves adaptive dimming without setting or modifying the temperature threshold for high-temperature highlighting, thus obtaining a dimmed image that meets the user's imaging style requirements.

[0019] Meanwhile, this invention limits the number of pixels by using a sample number threshold Gn, thereby increasing the influence weight of small high-temperature areas. It also uses contrast adjustment and image enhancement processing on the brightness mapping image X to highlight high-temperature areas while taking into account the details of the dimmed image, so that large high-temperature areas, small high-temperature areas, and high-temperature areas slightly higher than the ambient temperature can all be fully highlighted in the dimmed image. Attached Figure Description

[0020] Figure 1 This is a dimmed image obtained by dimming an infrared image using existing technology;

[0021] Figure 2 This is a flowchart illustrating the steps of the infrared image dimming method in this invention.

[0022] Figure 3 This is a dimmed image obtained after dimming an infrared image using the present invention;

[0023] Figure 4 This is a schematic diagram of the infrared image dimming system in this invention. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0025] Example 1

[0026] Figure 2 As shown, this embodiment provides a method for dimming infrared images, which includes the following steps:

[0027] S1. Determine the grayscale value V of each pixel in the infrared image, and obtain the number of samples n(V) for each grayscale value (samples are pixels) by drawing a grayscale histogram, etc., and obtain the dynamic range V of the infrared image. r Minimum grayscale value V min and the maximum grayscale value V max ;

[0028] Wherein, the dynamic range V r =Vmax -V min +1; Preferably, the infrared image is a preprocessed version of the original infrared image. The preprocessing includes filtering. For example, in this embodiment, image filtering can be performed based on any one of the following methods: Gaussian filtering, median filtering, bilateral filtering, nonlocal mean denoising, wavelet threshold denoising, total variational denoising, etc., thereby denoising the original infrared image and ensuring that the data sample points are smoother. At the same time, the infrared image is also a version of the original infrared image that has undergone point-dropping processing. The point-dropping processing includes: if the number of samples n(V) of the current gray value in the original infrared image is greater than the sample number threshold Gn, then the pixels exceeding the sample number threshold Gn are removed, so that the number of samples of the current gray value in the image after pixel-dropping is equal to the sample number threshold Gn.

[0029] The sample number threshold Gn can be determined according to the image resolution. The larger the image resolution, the larger the value of Gn. For example, in this embodiment, the range of the sample number threshold Gn is [300, 500]. Thus, the number of pixels can be limited by the sample number threshold Gn, thereby increasing the influence weight of small high-temperature areas and ensuring that small high-temperature areas can be highlighted in the dimmed image. For example, if the sample number threshold Gn is set to 300, and the number of pixels with a gray value of 100 is 350, then pixels exceeding the sample number threshold Gn will be removed, that is, 50 pixels with a gray value of 100 will be removed, and only 300 pixels with a gray value of 100 will be retained.

[0030] S2. Determine the pixel segmentation threshold V σ and brightness threshold D σ The pixel segmentation threshold V σ Brightness threshold D σ All values ​​are measured in grayscale.

[0031] Specifically, the pixel segmentation threshold V σ Obtain it through the following methods:

[0032] The histogram segmentation threshold Vσ1 and the dynamic range segmentation threshold Vσ2 are calculated based on the following formulas;

[0033]

[0034] V σ2 =V r Th+V min

[0035] Among them, H PLTTh is the grayscale histogram of the infrared image; Th is the adaptive threshold, and the larger the value of Th, the smaller the contrast and the greater the brightness in the high temperature area. In this embodiment, the adaptive threshold Th can be set according to the actual dimming effect, such as 0.3-1.0 (preferably 0.5-0.7).

[0036] The larger of the histogram segmentation threshold Vσ1 and the dynamic range segmentation threshold Vσ2 is used as the pixel segmentation threshold V. σ ;

[0037] In this embodiment, the histogram segmentation threshold Vσ1 can be determined by statistically analyzing the micro-pixel values ​​based on the histogram. It is used to make the contrast of the high-temperature area more obvious when the temperature of the high-temperature area is close to that of the background environment. The dynamic range segmentation threshold Vσ2 is calculated based on the macro dynamic range. Its purpose is to reduce the influence of the low-temperature background environment and increase the prominence of small-area high-temperature areas.

[0038] Furthermore, the brightness threshold D σ The value can be determined based on the actual dimming effect. In this embodiment, D σ The value range is [100, 150].

[0039] And, S3, in the infrared image, [V min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V max Pixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, to obtain a brightness-mapped image X (such as an 8-bit image);

[0040] Specifically, in this embodiment, pixel mapping is performed according to the following formula to obtain the brightness mapping image X:

[0041]

[0042] Among them, H PLT A is the grayscale histogram of the infrared image; s In infrared images, [V] min V σ The dynamic range occupied by pixels within a certain range in the luminance-mapped image X; A e In infrared images, [V] σ V max The dynamic range occupied by pixels within the range in the luminance-mapped image X; B s For the brightness-mapped image X, values ​​below the lower limit D of grayscale are... s The grayscale margin, the lower limit of grayscale value D sThe value range is [10, 20];

[0043] Since the mapping from a pixel to the grayscale range is generally linear, its expression can be constructed as Y = KX + B, where Y is the brightness mapping image (i.e., "X" in the above formula), and K is the slope, which can be represented by the histogram proportion of pixels in different ranges in the infrared image (i.e., ...). X represents the dynamic range (i.e., A) of the pixels within the corresponding range in the infrared image in the brightness-mapped image X. s A e ) represents B, where B is a constant term, and can be represented by B s D σ Furthermore, due to the infrared image, [V] min V σ ), [V σ V max Pixels within the range are segmented and mapped to the corresponding grayscale range. Therefore, K, X, and B are also segmented and taken in segments.

[0044] Furthermore, in the infrared image [V min V σ The dynamic range A occupied by pixels within a certain range in the luminance-mapped image X. s In infrared images [V σ V max The dynamic range A occupied by pixels within the range in the luminance-mapped image X. e And for the brightness-mapped image X, values ​​below the lower limit of grayscale D s gray margin B s It can be obtained through the following formula:

[0045]

[0046] Where S is the infrared image, [V min V max The dynamic range of pixels within the specified range in the luminance-mapped image X is defined as follows: D is the dynamic range of the luminance-mapped image X, and D = D1. e -D s +1, D e D s Let be the maximum and minimum grayscale values ​​in the luminance-mapped image X, respectively; and R be the dynamic range D of the luminance-mapped image X and the dynamic range V of the infrared image. r The smaller value in;

[0047] In this embodiment, the brightness threshold D is used. σ And the maximum grayscale value D in the brightness-mapped image X e Minimum grayscale value D sThe dynamic range of the luminance-mapped image X is determined segment by factors such as S ≥ D, so as to limit the dynamic range of the luminance-mapped image X to a predetermined range. For example, if S ≥ D σ -D s Then A s Restricted to D σ -D s This ensures that the pixels in the infrared image are linearly mapped as fully as possible into the brightness mapping image X, and that each high-temperature region is highlighted in the brightness mapping image X.

[0048] Therefore, this embodiment can be based on the pixel segmentation threshold V σ and brightness threshold D σ This method maps pixels within different ranges in an infrared image to different grayscale ranges. This process achieves adaptive dimming without setting or modifying the temperature threshold for high-temperature highlighting. Simultaneously, it limits the number of pixels by using a sample size threshold Gn, thereby increasing the influence weight of small-area high-temperature regions. Furthermore, it optimizes the dynamic range A... s A e The segmented values ​​are used to ensure that the dynamic range in the brightness mapping image X is limited to a predetermined range, so that each high-temperature region (including small high-temperature regions) in the infrared image can be highlighted in the brightness mapping image X.

[0049] Example 2:

[0050] The only difference between this embodiment and Embodiment 1 is that the dimming method further includes:

[0051] S4. Adjust the contrast of the brightness mapping image X based on the piecewise Gamma curve to obtain the contrast-adjusted image Y:

[0052]

[0053] Where Y is the pixel grayscale value after Gamma adjustment of the brightness mapping image X; γ d For a luminance-mapped image X, where luminance < luminance threshold D σ The region (i.e., X < D) σ The Gamma value during Gamma adjustment; γ u For a luminance-mapped image X, the luminance is greater than or equal to the luminance threshold D. σ The region (i.e., X≥D) σ The Gamma value during Gamma adjustment, where γ d The smaller the value, the lower the contrast in the low-temperature region, γ. u The larger the value, the greater the contrast in the high-temperature region;

[0054] And, S5, perform image enhancement processing on the contrast-adjusted image Y to obtain the final dimmed image, wherein the image enhancement processing includes:

[0055] If the infrared image is a preprocessed version of the original infrared image, then the pixel difference between the original infrared image and the infrared image obtained after filtering is superimposed on the contrast-adjusted image Y, and the contrast-adjusted image Y after superimposing the pixel difference is subjected to boundary protection processing. For example, if the gray value of a pixel in the contrast-adjusted image Y after superimposing the pixel difference exceeds 255, then the gray value of that pixel is assigned to 255.

[0056] And / or, the contrast-adjusted image Y (which may be a contrast-adjusted image Y without superimposed pixel differences or a contrast-adjusted image Y with superimposed pixel differences) is sharpened using a sharpener (such as a sharpener based on differential operators, a sharpener based on desharpening masks, a sharpener based on multi-scale analysis, etc.).

[0057] Therefore, in this embodiment, contrast adjustment and image enhancement processing can be used to highlight the high-temperature area while taking into account the details of the dimmed image, so that large-area high-temperature areas, small-area high-temperature areas, and high-temperature areas that are slightly higher than the ambient temperature can all be fully highlighted in the dimmed image.

[0058] Example 3:

[0059] This embodiment provides an infrared image dimming system that can implement the infrared image dimming method described in Embodiment 1, such as... Figure 4 As shown, the infrared image dimming system includes:

[0060] Gray-scale statistics module 1 is used to determine the gray-scale value V of each pixel in the infrared image, and to obtain the number of samples n(V) of each gray-scale value (samples are pixels) by drawing gray-scale histograms, etc., and to obtain the dynamic range V of the infrared image. r Minimum grayscale value V min Maximum grayscale value V max and average gray value V avg ;

[0061] Threshold setting module 2 is used to determine the pixel segmentation threshold V. σ And the brightness threshold Dσ, the process is the same as step S2;

[0062] Mapping module 3, which is used to map [V] from the infrared image. min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V maxPixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, a brightness mapping image X is obtained, and the process is the same as step S3;

[0063] The contrast adjustment module 4 adjusts the contrast of the brightness mapping image X based on the piecewise Gamma curve to obtain the contrast-adjusted image Y. The process is the same as step S4.

[0064] And, the image enhancement module 5, which is used to perform image enhancement processing on the contrast-adjusted image Y to obtain the final dimmed image, the process of which is the same as step S5.

[0065] In summary, this invention can be based on pixel segmentation threshold V σ and brightness threshold D σ This process maps pixels in different ranges of an infrared image to different grayscale ranges. It achieves adaptive dimming without setting or modifying the temperature threshold for high-temperature highlighting, thus obtaining a dimmed image that meets the user's imaging style requirements.

[0066] Meanwhile, this invention limits the number of pixels by using a sample size threshold Gn, thereby increasing the influence weight of small-area high-temperature regions, and by adjusting the dynamic range A... s A e The segmented values ​​are used to ensure that the dynamic range in the brightness mapping image X is limited to a predetermined range, so that each high-temperature region in the infrared image can be highlighted in the brightness mapping image X.

[0067] Furthermore, by adjusting the contrast of the brightness mapping image X and performing image enhancement processing, the details of the dimmed image are taken into account while highlighting the high-temperature areas, so that large-area high-temperature areas, small-area high-temperature areas, and high-temperature areas that are slightly higher than the ambient temperature can all be fully highlighted in the dimmed image.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for dimming infrared images, characterized in that, Includes the following steps: Determine the dynamic range V of the infrared image r Minimum grayscale value V min Maximum grayscale value V max ; Determine the pixel segmentation threshold V σ and brightness threshold D σ ; In the infrared image, [V min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V max Pixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, a brightness-mapped image X is obtained.

2. The dimming method as described in claim 1, characterized in that, The infrared image is a filtered image.

3. The dimming method as described in claim 1, characterized in that, The infrared image is an image obtained by performing a pixel-dropping process on the original infrared image. The pixel-dropping process includes: if the number of samples n(V) of the current grayscale value in the original infrared image is greater than the sample number threshold Gn, then the pixels exceeding the sample number threshold Gn are removed.

4. The dimming method as described in claim 1, characterized in that, The pixel segmentation threshold V σ Obtain it through the following methods: The histogram segmentation threshold Vσ1 and the dynamic range segmentation threshold Vσ2 are calculated based on the following formulas; ； V σ2 =V r Th+V min Among them, H PLT Th is the grayscale histogram of the infrared image; Th is the adaptive threshold. The larger of the histogram segmentation threshold Vσ1 and the dynamic range segmentation threshold Vσ2 is used as the pixel segmentation threshold V. σ .

5. The dimming method as described in claim 1, characterized in that, The pixel mapping is performed according to the following formula to obtain the brightness-mapped image X: ； Among them, H PLT A is the grayscale histogram of the infrared image; s In infrared images, [V] min V σ The dynamic range occupied by pixels within a certain range in the luminance-mapped image X; A e In infrared images, [V] σ V max The dynamic range occupied by pixels within the range in the luminance-mapped image X; B s For the brightness-mapped image X, values ​​below the lower limit D of grayscale are... s Gray margin.

6. The dimming method as described in claim 5, characterized in that, In infrared images [V min V σ The dynamic range A occupied by pixels within a certain range in the luminance-mapped image X. s In infrared images [V σ V max The dynamic range A occupied by pixels within the range in the luminance-mapped image X. e And for the brightness-mapped image X, values ​​below the lower limit of grayscale D s gray margin B s Obtain it using the following formula: ； Where S is the infrared image, [V min V max The dynamic range of pixels within the specified range in the luminance-mapped image X is defined as follows: D is the dynamic range of the luminance-mapped image X, and D = D1. e -D s +1, D e D s Let be the maximum and minimum grayscale values ​​in the luminance-mapped image X, respectively; and R be the dynamic range D of the luminance-mapped image X and the dynamic range V of the infrared image. r The smaller value in the range.

7. The dimming method as described in claim 1, characterized in that, The dimming method further includes: adjusting the contrast of the brightness mapping image X based on the Gamma curve to obtain a contrast-adjusted image Y.

8. The dimming method as described in claim 7, characterized in that, The contrast of the luminance-mapped image X is adjusted based on the following formula: ； Where Y is the pixel grayscale value after Gamma adjustment of the brightness mapping image X; γ d For a luminance-mapped image X, where luminance < luminance threshold D σ The Gamma value when Gamma is adjusted in the region; γ u For a luminance-mapped image X, the luminance is greater than or equal to the luminance threshold D. σ The Gamma value when adjusting Gamma in the region.

9. The dimming method as described in claim 7, characterized in that, The contrast-adjusted image Y is subjected to image enhancement processing, and the image enhancement processing includes: superimposing the pixel difference between the original infrared image and the filtered infrared image onto the contrast-adjusted image Y; and / or, sharpening the contrast-adjusted image Y.

10. A dimming system for infrared images, characterized in that, include: The grayscale statistics module is used to determine the number of samples n(V) for each grayscale value in the infrared image, and to obtain the dynamic range V of the infrared image. r Minimum grayscale value V min Maximum grayscale value V max ; The threshold setting module is used to determine the pixel segmentation threshold V. σ and brightness threshold D σ , And, a mapping module, which is used to map [V] from the infrared image. min V σ Pixels within the range of ) are mapped to values ​​less than the brightness threshold D. σ Within the grayscale range, [V σ V max Pixels within the range are mapped to a value greater than or equal to the brightness threshold D. σ Within the grayscale range, a brightness-mapped image X is obtained.

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