WO2022183333A1 - 红外图像传感器、红外图像处理方法及装置 - Google Patents

红外图像传感器、红外图像处理方法及装置 Download PDF

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Publication number
WO2022183333A1
WO2022183333A1 PCT/CN2021/078503 CN2021078503W WO2022183333A1 WO 2022183333 A1 WO2022183333 A1 WO 2022183333A1 CN 2021078503 W CN2021078503 W CN 2021078503W WO 2022183333 A1 WO2022183333 A1 WO 2022183333A1
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photosensitive
pixel
sub
pixels
types
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PCT/CN2021/078503
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English (en)
French (fr)
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张青涛
曹子晟
庹伟
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深圳市大疆创新科技有限公司
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Priority to PCT/CN2021/078503 priority Critical patent/WO2022183333A1/zh
Publication of WO2022183333A1 publication Critical patent/WO2022183333A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/20—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from infrared radiation only
    • H04N23/23—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from infrared radiation only from thermal infrared radiation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof

Definitions

  • the present application relates to the technical field of infrared images, and in particular, to an infrared image sensor, an infrared image processing method and device.
  • the photosensitive pixels of the current infrared sensors are all equally sensitive.
  • the infrared sensor can usually be set to different gain modes.
  • the user can Different temperature measurement accuracy and temperature measurement range need to be achieved by switching the mode of the infrared sensor.
  • the mode with high temperature measurement accuracy high-quality infrared images can be obtained, but the temperature measurement range is small, and it is impossible to measure the temperature of high-temperature objects.
  • a larger temperature measurement range can be obtained to achieve temperature measurement of high-temperature objects, but the quality of the collected infrared images is very low, and the temperature measurement accuracy is also very low. Because the current infrared sensor cannot take into account high temperature measurement accuracy, high temperature measurement range and high viewing quality at the same time, it brings a lot of inconvenience to users.
  • the present application provides an infrared image sensor, an infrared image processing method and device.
  • an infrared image sensor includes a photosensitive pixel array, and the photosensitive pixel array includes at least two types of photosensitive pixels, wherein different types of photosensitive pixels correspond to different photosensitive pixels ability.
  • an infrared image acquisition device includes the infrared image sensor mentioned in the first aspect above.
  • an image processing method wherein the infrared image includes at least two types of pixel points, and the pixel values of different types of pixel points are acquired by photosensitive pixels with different photosensitive capabilities, and the method includes: :
  • the temperature of the object corresponding to the target image area is determined according to the pixel values of the at least two types of pixel points in the target image area.
  • an infrared image processing method wherein the infrared image includes at least two types of pixel points, and the pixel values of different types of pixel points are collected by photosensitive pixels with different photosensitive capabilities.
  • a target image is obtained based on the at least two sub-images.
  • an infrared image processing device for processing an infrared image, wherein the infrared image includes at least two types of pixel points, and the pixel values of the different types of pixel points pass through the photosensitive pixels with different photosensitive capabilities.
  • the device includes a processor, a memory, and a computer program stored on the memory for execution by the processor, and the processor implements the following steps when executing the computer program:
  • the temperature of the object corresponding to the target image area is determined according to the pixel values of the at least two types of pixel points in the target image area.
  • an infrared image processing device for processing an infrared image, wherein the infrared image includes at least two types of pixel points, and the pixel values of the different types of pixel points pass through the photosensitive pixels with different photosensitive capabilities.
  • the device includes a processor, a memory, and a computer program stored on the memory for execution by the processor, and the processor implements the following steps when executing the computer program:
  • a target image is obtained based on the at least two sub-images.
  • a seventh aspect of the present application there is provided a computer-readable storage medium on which computer program instructions are stored.
  • the instructions are executed by a processor, the infrared image processing method mentioned in the third aspect or the fourth aspect can be implemented. .
  • an infrared image sensor includes a photosensitive pixel array, and the photosensitive pixel array includes at least two kinds of photosensitive pixels, and different types of photosensitive pixels have different photosensitive capabilities.
  • the signal-to-noise ratio, temperature measurement accuracy and temperature measurement range corresponding to the photosensitive pixels are more flexible and changeable, and the infrared sensor can be taken into account in a single exposure process. Higher temperature measurement accuracy, larger temperature measurement range and higher image quality, no need for users to switch modes during use.
  • FIG. 1 is a schematic diagram of a photosensitive pixel array according to an embodiment of the present application.
  • FIG. 2 is a schematic diagram of the distribution of different types of photosensitive pixels in a photosensitive pixel array according to an embodiment of the present application.
  • FIG. 3 is a schematic diagram of the distribution of different types of photosensitive pixels in a photosensitive pixel array according to an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a sub-array in a photosensitive pixel array according to an embodiment of the present application.
  • FIG. 5 is a flowchart of another infrared image processing method according to an embodiment of the present application.
  • FIG. 6 is a flowchart of another infrared image processing method according to an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a logical structure of an infrared image processing apparatus according to an embodiment of the present application.
  • FIG. 8 is a schematic diagram of a logical structure of another infrared image processing apparatus according to an embodiment of the present application.
  • each photosensitive pixel is equally photosensitive, that is, the photosensitive ability of each photosensitive pixel is the same.
  • the infrared sensor can usually be set to different temperature measurement modes (under different temperature measurement modes, the electrical signals converted into the optical signals received by the photosensitive pixels are amplified by different multiples) processing), for example, current infrared sensors usually have a high gain mode and a low gain mode. In the high-gain mode, the infrared sensor has high temperature measurement accuracy, high signal-to-noise ratio, and the captured image viewing quality is better and clearer.
  • the temperature measurement range is relatively narrow.
  • the temperature measurement range in the mode is -40 ⁇ 150°C, and the accuracy is about ⁇ 2°C.
  • the infrared sensor In the low-gain mode, the infrared sensor has a wide temperature measurement range, but the temperature measurement accuracy is low, the signal-to-noise ratio is low, and the observation image is blurred and unclear.
  • the temperature measurement range of most infrared sensors in the low-gain mode is - 40 ⁇ 550°C, the accuracy is ⁇ 5°C or worse.
  • the current infrared sensor cannot take into account the temperature measurement accuracy, temperature measurement range and image quality, and needs to switch modes during use, which brings a lot of inconvenience to users.
  • an embodiment of the present application provides an infrared image sensor, the infrared image sensor includes a photosensitive pixel array, and the photosensitive pixel array includes at least two types of photosensitive pixels, and different types of photosensitive pixels correspond to different photosensitive capabilities, as shown in FIG. 1
  • a photosensitive pixel array provided by an embodiment of the present application is shown, which includes two types of photosensitive pixels, namely N and L shown in the figure.
  • the photosensitive pixels can be used to receive infrared light radiated by external objects, and then convert the received infrared light signals into electrical signals, and output the pixel value corresponding to each pixel. Based on the pixel value, the temperature information corresponding to each pixel point can be determined.
  • different types of photosensitive pixels have different photosensitive capabilities, for the same intensity of infrared light signal, different types of photosensitive pixels experience different light intensities, and then the converted electrical signal intensities are also different.
  • different types of photosensitive pixels can be collected to obtain different signal-to-noise ratios, or different temperature measurement accuracy, or different temperature measurement ranges, or different signal-to-noise ratios, temperature measurement accuracy, and temperature measurement ranges.
  • pixel value so that the same image collected can include pixels with different temperature measurement accuracy, different temperature measurement range, and different signal-to-noise ratios.
  • the temperature measurement range, temperature measurement accuracy and signal-to-noise ratio settings of the sensor are more flexible and changeable, and the temperature measurement range, temperature measurement accuracy and image quality can be considered in a single exposure process.
  • the types of photosensitive pixels can be set to two, three or even more types according to actual needs, and the number of photosensitive pixels of different types can be the same or different.
  • the difference in photosensitive ability between different types of photosensitive pixels can also be set according to actual needs, and the temperature measurement accuracy and temperature measurement range corresponding to different photosensitive pixels can also be set according to actual needs, which are not limited in the embodiments of the present application.
  • the infrared sensor may also include other general components for realizing infrared imaging and temperature measurement, which will not be described here.
  • the settings of the temperature measurement range, temperature measurement accuracy and signal-to-noise ratio of the infrared sensor can be more flexible and changeable. , the temperature measurement range, temperature measurement accuracy and image quality can be taken into account during a single exposure process, and there is no need for users to switch modes during use, which is more convenient for users to use.
  • the exposure time of the photosensitive pixels can be changed to obtain photosensitive pixels with different photosensitive capabilities.
  • different types of photosensitive pixels can be controlled to have different exposure durations in each exposure process of the infrared sensor, so that in each exposure process, different types of photosensitive pixels receive different amounts of infrared light to achieve different photosensitive capabilities. .
  • the longer the exposure time the stronger the photosensitive ability of the photosensitive pixel.
  • the exposure duration of the photosensitive pixel N in a single exposure process can be controlled to be 0.2s, and the exposure duration of the photosensitive pixel L in a single exposure process can be controlled to be 0.1s to obtain the difference. photosensitive ability.
  • the photosensitive pixels can also have different photosensitive capabilities by changing the physical properties of the photosensitive pixels themselves.
  • the physical property may be any property related to the responsiveness of the photosensitive pixel to infrared light.
  • the physical property may be one or more of the area of the photosensitive pixel, the material of the photosensitive pixel, or the light transmittance of the photosensitive pixel.
  • different photosensitive areas may be set for different types of photosensitive pixels, so that the amount of infrared light received by different types of photosensitive pixels is different during each exposure process.
  • different materials can also be used for different types of photosensitive pixels, and photosensitive pixels of different materials have different response characteristics to infrared light.
  • filters with different transmittances to infrared light can also be set on different types of photosensitive pixels, so that the amount of infrared light received by different types of photosensitive pixels is different, thereby forming differentiated photosensitive capabilities.
  • the intensity of infrared light felt by different types of photosensitive pixels is also different, so the intensity of the converted electrical signal is also different, which can be expressed as Different types of photosensitive pixels have different temperature measurement precisions and different temperature measurement ranges.
  • different types of photosensitive pixels may correspond to different temperature measurement accuracy, or different types of photosensitive pixels may correspond to different temperature measurement ranges, or different types of photosensitive pixels may correspond to different temperature measurement accuracy and temperature measurement accuracy scope.
  • the stronger the photosensitive ability of the photosensitive pixels on the photosensitive array the higher the corresponding temperature measurement accuracy, and the smaller the corresponding temperature measurement range.
  • the stronger the photosensitive ability of the photosensitive pixel the stronger the light signal it feels when the same infrared light reaches the photosensitive pixel, and the stronger the converted electrical signal, so the temperature measurement accuracy can be higher.
  • the stronger the converted electrical signal is, in order to make the amplified signal not exceed the signal strength that the signal processing element can handle, the amplification factor is also limited, resulting in a relatively small temperature measurement range.
  • the number of different types of photosensitive pixels in the photosensitive array on the infrared sensor can be set to be the same or different, which can be set according to actual needs.
  • the temperature distribution ranges of the objects in the scene are different. Some temperature ranges have more and more dense objects, and some temperature ranges have fewer objects.
  • the corresponding photosensitive pixels should be as many as possible (that is, the number of photosensitive pixels capable of measuring the temperature range should be as many as possible) to ensure the accuracy of the temperature measurement results for most objects.
  • the number of photosensitive pixels corresponding to this temperature range may be appropriately less, and the temperature measurement requirements of objects in this temperature range may also be met.
  • the number of each type of photosensitive pixels may be determined based on the temperature measurement accuracy and/or temperature measurement range corresponding to each type of photosensitive pixels.
  • the denser the distribution of the temperature of the temperature-measured object within a certain temperature measurement range the greater the number of photosensitive pixels corresponding to the temperature measurement range, that is, the photosensitive pixels with temperature measurement capability for the temperature measurement range.
  • the temperature of the objects in the temperature measurement scene is mostly distributed in the temperature range of -40 to 150 °C, and only a few exceed 150 °C. Therefore, the number of photosensitive pixels N can be set to be more, and the number of photosensitive pixels L can be less.
  • the photosensitive pixel array may include two types of photosensitive pixels: first photosensitive pixels and second photosensitive pixels.
  • the temperature measurement accuracy corresponding to the pixel is lower than the temperature measurement accuracy corresponding to the second photosensitive pixel
  • the temperature measurement range corresponding to the first photosensitive pixel is greater than the temperature measurement range corresponding to the second photosensitive pixel
  • the number of the first photosensitive pixel is less than that of the second photosensitive pixel. the number of pixels.
  • the first photosensitive pixel is used to achieve higher temperature measurement accuracy
  • the second photosensitive pixel is used to achieve a larger temperature measurement range.
  • current infrared sensors generally include a low gain mode and a high gain mode.
  • the temperature measurement range in the low gain mode is -40 to 550°C, and the accuracy is about ⁇ 5°C, while the temperature measurement range in the high gain mode is - 40 ⁇ 150°C, the accuracy is about ⁇ 2°C, the low gain mode can achieve a high temperature measurement range, and the high gain mode can achieve high temperature measurement accuracy.
  • the infrared sensor can take into account high temperature measurement range and high temperature measurement accuracy without mode switching
  • two types of photosensitive pixels can be set in the photosensitive pixel array of the infrared sensor, wherein the first photosensitive pixel can be aligned with the low gain mode, The temperature measurement range can reach -40 ⁇ 550°C, the accuracy is about ⁇ -5°C, and the second photosensitive pixel can be aligned with the high gain mode, the temperature measurement range can reach -40 ⁇ 150°C, and the accuracy is about ⁇ 2°C.
  • the first photosensitive pixel can be aligned with the low gain mode
  • the temperature measurement range can reach -40 ⁇ 550°C
  • the accuracy is about ⁇ -5°C
  • the second photosensitive pixel can be aligned with the high gain mode
  • the temperature measurement range can reach -40 ⁇ 150°C
  • the accuracy is about ⁇ 2°C.
  • the number of the second photosensitive pixels may be greater than that of the first photosensitive pixels.
  • the number of second photosensitive pixels accounts for 75%
  • the number of first photosensitive pixels accounts for 25%.
  • the photosensitive pixel array may include two types of photosensitive pixels: a first photosensitive pixel and a second photosensitive pixel pixel, the temperature measurement accuracy corresponding to the first photosensitive pixel is higher than the temperature measurement accuracy of the second photosensitive pixel, the temperature measurement range corresponding to the first photosensitive pixel is smaller than the temperature measurement range of the second photosensitive pixel, and the number of the first photosensitive pixel is less than The number of second photosensitive pixels.
  • the first photosensitive pixel is used to achieve ultra-high precision temperature measurement of an object (eg, human body) within a specific temperature range
  • the second photosensitive pixel is used to achieve relatively high temperature measurement accuracy for common objects.
  • the temperature measurement accuracy in high gain mode is still not enough for some temperature measurement objects.
  • the temperature measurement accuracy in high gain mode is About ⁇ 2°C, but for human body temperature measurement, the accuracy is far from enough, which requires higher temperature measurement accuracy.
  • this mode that requires ultra-high temperature measurement accuracy the ultra-high gain mode. It can realize ultra-high-precision temperature measurement of objects within a specific temperature range. Taking human body temperature measurement as an example, the temperature range can be 30 to 45 degrees with an accuracy of ⁇ 0.5 degrees. Therefore, two types of pixels can be set.
  • the first photosensitive pixel can be aligned with the ultra-high gain mode, and the second photosensitive pixel can be aligned with the high-gain mode, so that there is no need to switch modes, which can achieve high temperature measurement accuracy, and can achieve specific objects. of ultra-precise temperature measurement. Meanwhile, since most objects only need high-precision temperature measurement, and only a few objects need ultra-high-precision temperature measurement, the number of first photosensitive pixels may be less than the number of second photosensitive pixels. For example, in some embodiments, the number of first photosensitive pixels accounts for 25%, and the number of second photosensitive pixels accounts for 75%.
  • the photosensitive pixel array may include three types of photosensitive pixels: the first photosensitive pixel , the second photosensitive pixel and the third photosensitive pixel, the temperature measurement accuracy corresponding to the first photosensitive pixel is lower than the temperature measurement accuracy of the second photosensitive pixel and the temperature measurement range corresponding to the first photosensitive pixel is greater than the temperature measurement range of the second photosensitive pixel, The temperature measurement accuracy corresponding to the third photosensitive pixel is higher than that of the second photosensitive pixel, and the temperature measurement range corresponding to the third photosensitive pixel is smaller than the temperature measurement range of the second photosensitive pixel.
  • the number of the first photosensitive pixel and the number of the third photosensitive pixel are both small. on the number of the second photosensitive pixels. Among them, the first photosensitive pixel is used to achieve higher temperature measurement accuracy, the second photosensitive pixel is used to achieve a larger temperature measurement range, and the third photosensitive pixel is used to achieve ultra-high precision temperature measurement for objects in a specific temperature range.
  • the first photosensitive pixel is aligned with the low gain mode, which can achieve a high temperature measurement range.
  • the second photosensitive pixel is aligned with the high gain mode, which can achieve high temperature measurement accuracy and high viewing quality
  • the third photosensitive pixel is aligned with the ultra-high gain mode, which can achieve ultra-high-precision temperature measurement of objects in a specific temperature range.
  • the number of the second photosensitive pixels may be greater than the number of the first photosensitive pixels and the third photosensitive pixels.
  • the number of the second photosensitive pixels accounts for 50%, and the number of the first photosensitive pixels and the third photosensitive pixels each account for 25%.
  • the photosensitive pixel array includes at least two types of photosensitive pixels
  • the arrangement of different types of photosensitive pixels will also have a certain impact on temperature measurement accuracy and image quality.
  • the same type of photosensitive pixels should be distributed as far as possible in the photosensitive pixel array (as shown in Figure 1), rather than one type of photosensitive pixels should be concentrated in one area (as shown in Figure 2).
  • the pixel value of the pixel corresponding to each object includes the image value collected by different types of photosensitive pixels, so that the pixel value collected by the appropriate photosensitive pixel can be used for further temperature measurement, or based on different types of photosensitive pixels.
  • the photosensitive pixels can get better quality viewing images.
  • each A photosensitive pixel may be distributed among a plurality of second photosensitive pixel arrays, as shown in FIG. 3 , L in the figure represents the first photosensitive pixel, and N represents the second photosensitive pixel.
  • each first photosensitive pixel or each third photosensitive pixel may be distributed among a plurality of second photosensitive pixels.
  • the at least two types of photosensitive pixels in the photosensitive pixel array may be uniformly distributed or randomly distributed according to a preset arrangement rule.
  • the photosensitive pixel array including two types of photosensitive pixels (photosensitive pixel N and photosensitive pixel L) as an example, the two types of photosensitive pixels can be arranged alternately, or every four photosensitive pixels N can surround one photosensitive pixel L, or each photosensitive pixel N can be surrounded by a photosensitive pixel L.
  • Two photosensitive pixels N are followed by one photosensitive pixel L, etc., wherein the specific arrangement rules can be set based on the number of different types of photosensitive pixels and actual requirements.
  • the two types of photosensitive pixels can also be randomly arranged. It is only necessary to ensure that the at least two types of photosensitive pixels are included in a certain range of pixel areas as far as possible.
  • the photosensitive pixel array may be divided into a plurality of sub-arrays, and each sub-array includes the at least two types of photosensitive pixels.
  • the photosensitive pixel array can be divided into a plurality of rectangular sub-arrays, each sub-array includes The three types of photosensitive pixels.
  • the size of the sub-array can be set based on actual requirements. The smaller the sub-array, the more uniform the distribution of different types of photosensitive pixels in the photosensitive array.
  • the number of each type of photosensitive pixels in each sub-array may be the same. For example, if there are three types of photosensitive pixels, N, L, and H, each sub-array includes N, L, and H, and the number of the three photosensitive pixels is the same. Of course, the number of the three types of photosensitive pixels in each sub-array may also be inconsistent, for example, some sub-arrays may have more N, and some sub-arrays may have more L.
  • the at least two types of photosensitive pixels are arranged in the same manner in each sub-array. For example, if there are three types of photosensitive pixels, N, L, and H, each sub-array includes N, L, and H, and the three photosensitive pixels are arranged in the same way.
  • an embodiment of the present application also provides an infrared image acquisition device, where the infrared image acquisition device includes the infrared image sensor described in the above embodiments.
  • the photosensitive pixels on the photosensitive pixel array can be inconsistent in their photosensitive capabilities, and there is no need to uniformly and equally photosensitive.
  • the infrared image collected by this kind of infrared sensor since the image includes different types of pixels, different types of pixels are collected by photosensitive pixels with different photosensitive capabilities, so the temperature measurement accuracy and temperature measurement range of these different types of pixels are , the signal-to-noise ratio will also be different, so the temperature of the object can be measured more accurately based on the characteristics of these different types of pixels.
  • an embodiment of the present application provides an infrared image processing method, which is suitable for processing an infrared image including at least two types of pixel points to determine the temperature of an object corresponding to each image area in the infrared image.
  • the pixel values of different types of pixel points are obtained by collecting pixel points with different photosensitive capabilities.
  • the method includes the following steps:
  • the pixel values of different types of pixels can be collected by the photosensitive pixels with different photosensitive capabilities, and the photosensitive pixels with different photosensitive capabilities can correspond to different temperature measurement ranges and/or temperature measurement accuracy. . Because the temperature measurement accuracy and temperature measurement range corresponding to different types of pixels can be different, and the objects corresponding to different image areas in the infrared image have different requirements for the temperature measurement range and temperature measurement accuracy. Therefore, when determining the temperature of the object corresponding to the target image area in the infrared image, the pixel values of different types of pixels in the target image area can be obtained first, and then the characteristics of different types of pixels and their pixel values can be comprehensively determined. The temperature of the object corresponding to the target image area. For example, the temperature of the object may be determined by selecting a pixel with a more accurate temperature measurement result, or by combining the temperatures determined by different types of pixels to obtain the final temperature of the object.
  • the temperature measurement accuracy and temperature measurement range corresponding to different types of pixels are different, and the objects corresponding to different image areas in the infrared image have different requirements for the temperature measurement range and temperature measurement accuracy. Therefore, when using the above at least two types of pixel points to determine the temperature of the object corresponding to the target image area, in order to measure the temperature more accurately, it is possible to first determine the temperature of the object corresponding to the at least two types of pixel points from the at least two types of The pixel points of the first target type in the pixel points of the first target type are then used to determine the temperature of the object corresponding to the target image area by using the pixel values of the pixel points of the first target type.
  • the temperature measurement range and temperature measurement accuracy corresponding to the pixel points of the first target type are more in line with the requirements of the object corresponding to the target image area, that is, the pixel points of the first target type can be used to more accurately determine the object corresponding to the target image area. temperature.
  • the temperature measurement ranges corresponding to different types of pixels are different, in some scenarios, when the temperature of the object determined based on a certain type of pixels has a high degree of saturation, the The temperature of the object is already close to the upper limit of the temperature measurement range corresponding to this type of pixel, so the temperature of the object determined by this type of pixel is likely to be inaccurate. In this case, a pixel with a lower degree of saturation should be selected. Determines the temperature of this object. Therefore, in some embodiments, when the pixel points of the first target type are determined from the at least two types of pixel points according to the pixel values of the at least two types of pixel points, the pixel points of the first target type may be determined according to the at least two types of pixel points.
  • the pixel value of each type of pixel in the object determines the temperature of the object, and based on the determined temperature and the temperature measurement range of each type of pixel, the corresponding saturation degree of this type of pixel is determined, based on the saturation degree from The pixel point of the first target type is determined from the at least two types of pixel points.
  • the temperature measurement range corresponding to pixel N is -40 ⁇ 150°C
  • the temperature measurement range corresponding to pixel L is -40 ⁇ 200°C
  • the temperature of object A is determined to be 149°C according to the pixel value of pixel point N
  • the temperature of object A is determined to be 154°C according to the pixel value of pixel point L
  • object A is determined according to the pixel value of pixel point N.
  • the temperature is close to saturation, that is, very close to the upper limit of the temperature measurement range. Therefore, the temperature determined according to the pixel point N is likely to be inaccurate.
  • the pixel point L should be used as the pixel point of the first target type to determine the object A. temperature.
  • the pixel point of the first target type when determining the pixel point of the first target type from the at least two types of pixel points according to the pixel values of the at least two types of pixel points, the pixel point of the first target type may The pixel value of the point determines the temperature range of the object, and determines the type of the object based on the temperature range of the object, and then according to the type of the object and the at least two types of pixels corresponding to the temperature measurement accuracy from at least two types of pixels. The pixel points of the first target type are determined in the points.
  • the temperature measurement accuracy corresponding to pixel N is ⁇ 0.5°C
  • the temperature measurement accuracy corresponding to pixel L is ⁇ 2°C.
  • the temperature range of the object A is determined to be 35-37 °C. Therefore, based on this temperature range, it can be determined that the object A is likely to be a human body.
  • the pixel point N is used as the pixel point of the first target type to determine the temperature of the object A.
  • infrared images can also be used for sighting.
  • infrared images are required to have the highest possible picture quality. Since different types of pixels are collected by photosensitive pixels with different photosensitive capabilities, the signal-to-noise ratios corresponding to different types of pixels are also different, that is, the sharpness of images obtained from different types of pixels is different.
  • the infrared image can be processed based on the characteristics of different types of pixels to obtain a clearer image.
  • the pixel value of a pixel with a high signal-to-noise ratio can be used to correct the pixel value of a pixel with a low signal-to-noise ratio to obtain an image with better image quality, and the infrared image can also be filtered.
  • the weight of each pixel can be determined based on the signal-to-noise ratio of each pixel.
  • the weight of a pixel with a high signal-to-noise ratio can be appropriately larger, and the filtering process can include various edge-preserving filtering processes.
  • high-quality viewing images can also be obtained by fusing pixel values of different types of pixels.
  • At least two frames of sub-images may be obtained according to at least two types of pixel points in the infrared image, wherein each frame of the sub-image is obtained based on the same type of pixel points, and then based on the at least two frames of sub-images Get the target image. Since the image quality and definition of the sub-images obtained from different types of pixels are different, the obtained sub-images of different types of pixels can be fused to obtain a target image with higher image quality.
  • the pixel sizes of the images formed by each type of pixels may also be different.
  • the same Type of pixels and perform upsampling processing on these pixels to obtain a sub-image with a specified pixel size, which is convenient for subsequent processing of the sub-image.
  • the pixel size of the sub-image can be set according to actual requirements, for example, it can be the same as the pixel size of the sub-image composed of the most types of pixel points, or it can be the same as the pixel size of the infrared image.
  • the target image when the target image is obtained from the sub-image, the sub-image formed by the type of pixel with the largest number of pixels can be used as a guide to process other sub-images. Therefore, in some embodiments, when the target image is obtained based on at least two sub-images, the target sub-image may be determined from the at least two sub-images, wherein the target sub-image is obtained based on the pixels of the second target type, and the first sub-image is obtained from the pixels of the second target type.
  • the second target type is the type corresponding to the largest number of pixels in the infrared image, and then the target sub-image is used as the guide image, and the guide filtering is performed on other sub-images, and then the other sub-images and the target sub-image after the guide filtering are processed. fused to get the target image.
  • pyramid decomposition may be performed on the at least two sub-images first, and then the at least two frames after pyramid decomposition are decomposed into a pyramid. The sub-images are fused on the corresponding layers to obtain the target image.
  • the pixel size of the final target image may be consistent with the pixel size of the infrared image.
  • the same type of pixels can be extracted, and then upsampled into sub-images with the same pixel size as the infrared image, and the sub-images can be fused to obtain the target image.
  • the same type of pixels can also be extracted, and then up-sampled to a sub-image with the same pixel size as the sub-image formed by the type of pixels with the largest number.
  • the target image with the same pixel size of the infrared image may be consistent with the pixel size of the infrared image.
  • an infrared image includes three types of pixels, pixel N, pixel L, and pixel H.
  • the pixel values of the three types of pixels are collected by photosensitive pixels with different photosensitive capabilities. It has higher signal-to-noise ratio and higher temperature measurement accuracy, pixel point L has lower signal-to-noise ratio, but has a larger temperature measurement range, pixel point H has ultra-high signal-to-noise ratio and ultra-high temperature measurement range.
  • Temperature accuracy which can be used for ultra-high-precision temperature measurement of objects in a specific temperature range (for example, human body temperature measurement).
  • the number of pixels N accounts for 50%, the number of pixels H and N accounts for 25%, and the three types of pixels are evenly distributed in the image.
  • the pixel points N in the image can be extracted to form a sub-image N, and then the pixel points L and H are extracted respectively, and up-sampled into a sub-image L with the same size as the sub-image N. and sub-image H, and then use the sub-image N as a guide map to perform guided filtering on the sub-image L and the sub-image H respectively to obtain the filtered sub-image L and the filtered sub-image H, and then the sub-image N, the sub-image L and the sub-image H can be obtained.
  • the image H is fused, and after fusion, it is upsampled into a target image with the same size as the infrared image.
  • the infrared image is acquired by an infrared sensor, the infrared sensor includes a photosensitive pixel array, and the photosensitive pixel array includes at least two types of photosensitive pixels, wherein different types of photosensitive pixels correspond to different photosensitive pixels ability.
  • the different photosensitive capabilities are obtained by changing the exposure time of the photosensitive pixels; and/or
  • the different photosensitive capabilities are obtained by changing the physical properties of the photosensitive pixels.
  • the physical properties include the area of the photosensitive pixel, the material of the photosensitive pixel, and/or the light transmittance of the photosensitive pixel.
  • different types of photosensitive pixels correspond to different temperature measurement precisions and/or temperature measurement ranges.
  • the stronger the photosensitive ability of the photosensitive pixel the higher the temperature measurement accuracy, and the smaller the temperature measurement range.
  • the number of each type of photosensitive pixels is determined based on the temperature measurement accuracy and/or temperature measurement range corresponding to each type of photosensitive pixels.
  • the denser the distribution of the temperature of the temperature-measured object within the temperature measurement range the greater the number of photosensitive pixels corresponding to the temperature measurement range.
  • the photosensitive pixel array may be divided into a plurality of sub-arrays, and each sub-array includes the at least two types of photosensitive pixels.
  • the number of photosensitive pixels of each type is the same in each of the sub-arrays.
  • the at least two types of photosensitive pixels are arranged in the same manner in each of the sub-arrays.
  • the photosensitive capabilities of the photosensitive pixels on the photosensitive pixel array can be inconsistent, and there is no need for uniform and equal photosensitive.
  • the infrared image collected by this kind of infrared sensor since the image includes different types of pixels, different types of pixels are collected by photosensitive pixels with different photosensitive capabilities, so the signal-to-noise ratios of these different types of pixels are also different.
  • the image quality of the formed images will also be different. Therefore, pixels with a high signal-to-noise ratio can be used to correct pixels with a low signal-to-noise ratio to obtain an image with higher image quality. Therefore, while obtaining higher temperature measurement accuracy, the image quality of the infrared image can also be taken into consideration.
  • an embodiment of the present application provides an infrared image processing method, which is suitable for processing an infrared image including at least two types of pixel points, wherein the pixel values of different types of pixel points are determined by different photosensitive abilities.
  • the pixel points are collected.
  • the method includes the following steps:
  • the image quality of sub-images obtained based on different types of pixels is also different. Therefore, the same type of pixels in the infrared image can be extracted to obtain sub-images, and the sub-images obtained by different types of pixels have different signal-to-noise ratios and clarity. The sub-image with high image quality is corrected to obtain the target image with better image quality.
  • obtaining the target image based on the at least two sub-images includes:
  • the target sub-image is obtained based on the pixel point of the second target type, and the second target type is the type corresponding to the largest number of pixels in the infrared image;
  • the other sub-images processed by the guided filtering and the target sub-image are fused to obtain the target image.
  • obtaining the target image based on the at least two sub-images includes:
  • the at least two frames of sub-images after pyramid decomposition are fused on corresponding layers to obtain the target image.
  • the pixel size of the target image is the same as the pixel size of the infrared image.
  • an embodiment of the present application provides an infrared image processing device.
  • the infrared image includes at least two types of pixel points, and the pixel values of different types of pixel points pass through the photosensitive pixels with different photosensitive capabilities.
  • the device 70 includes a processor 71, a memory 72, and a computer program stored in the memory for execution by the processor.
  • the processor 71 executes the computer program, the following steps can be implemented:
  • the temperature of the object corresponding to the target image area is determined according to the pixel values of the at least two types of pixel points in the target image area.
  • the processor when the processor is configured to determine the temperature of the object corresponding to the target image area according to the pixel values of the at least two types of pixel points in the target image area, the processor is specifically configured to:
  • a pixel point of a first target type is determined from the at least two types of pixel points according to pixel values of the at least two types of pixel points, wherein the object determined by using the pixel point of the first target type
  • the accuracy of the temperature of the object is higher than the accuracy of the temperature of the object determined using other types of pixels;
  • the temperature of the object corresponding to the target image area is determined according to the pixel value of the pixel point of the first target type.
  • the processor when the processor is configured to determine a pixel of the first target type from the at least two types of pixels according to pixel values of the at least two types of pixels, the processor is specifically configured to:
  • a pixel point of the first target type is determined from the at least two types of pixel points based on the degree of saturation.
  • the processor when the processor is configured to determine a pixel of the first target type from the at least two types of pixels according to pixel values of the at least two types of pixels, the processor is specifically configured to:
  • the pixel points of the first target type are determined from the at least two types of pixel points based on the type of the object and the corresponding temperature measurement accuracy of the at least two types of pixel points.
  • the processor is further configured to:
  • a target image is obtained based on the at least two sub-images.
  • the processor when configured to obtain the target image based on the at least two sub-images, it is specifically configured to:
  • a target sub-image from the at least two sub-images and the target sub-image is obtained based on pixels of a second target type, and the second target type is the type corresponding to the largest number of pixels in the infrared image;
  • the other sub-images processed by the guided filtering and the target sub-image are fused to obtain the target image.
  • the processor when configured to obtain the target image based on the at least two sub-images, it is specifically configured to:
  • the at least two frames of sub-images after pyramid decomposition are fused on corresponding layers to obtain the target image.
  • the pixel size of the target image is the same as the pixel size of the infrared image.
  • the infrared image is acquired by an infrared sensor, the infrared sensor includes a photosensitive pixel array, and the photosensitive pixel array includes at least two types of photosensitive pixels, wherein different types of photosensitive pixels correspond to different photosensitive pixels ability.
  • the different photosensitive capabilities are obtained by changing the exposure time of the photosensitive pixels; and/or
  • the different photosensitive capabilities are obtained by changing the physical properties of the photosensitive pixels.
  • the physical properties include the area of the photosensitive pixel, the material of the photosensitive pixel, and/or the light transmittance of the photosensitive pixel.
  • different types of photosensitive pixels correspond to different temperature measurement precisions and/or temperature measurement ranges.
  • the stronger the photosensitive ability of the photosensitive pixel the higher the temperature measurement accuracy, and the smaller the temperature measurement range.
  • the number of each type of photosensitive pixels is determined based on the temperature measurement accuracy and/or temperature measurement range corresponding to each type of photosensitive pixels.
  • the denser the distribution of the temperature of the temperature-measured object within the temperature measurement range the greater the number of photosensitive pixels corresponding to the temperature measurement range.
  • the photosensitive pixel array may be divided into a plurality of sub-arrays, each of which includes the at least two types of photosensitive pixels.
  • the number of photosensitive pixels of each type is the same in each of the sub-arrays.
  • the at least two types of photosensitive pixels are arranged in the same manner in each of the sub-arrays.
  • the embodiment of the present application also provides another infrared image processing device.
  • the infrared image includes at least two types of pixels, and the pixel values of different types of pixels Pixel acquisition is obtained
  • the device includes a processor 81, a memory 82, and a computer program stored in the memory 82 for the processor 81 to execute.
  • the processor 81 executes the computer program, the following steps can be implemented:
  • a target image is obtained based on the at least two sub-images.
  • the processor when configured to obtain the target image based on the at least two sub-images, it is specifically configured to:
  • a target sub-image from the at least two sub-images and the target sub-image is obtained based on pixels of a second target type, and the second target type is the type corresponding to the largest number of pixels in the infrared image;
  • the other sub-images processed by the guided filtering and the target sub-image are fused to obtain the target image.
  • the processor when configured to obtain the target image based on the at least two sub-images, it is specifically configured to:
  • the at least two frames of sub-images after pyramid decomposition are fused on corresponding layers to obtain the target image.
  • the pixel size of the target image is the same as the pixel size of the infrared image.
  • an embodiment of this specification further provides a computer storage medium, where a program is stored in the storage medium, and when the program is executed by a processor, the infrared image processing method in any of the foregoing embodiments is implemented.
  • Embodiments of the present specification may take the form of a computer program product embodied on one or more storage media having program code embodied therein, including but not limited to disk storage, CD-ROM, optical storage, and the like.
  • Computer-usable storage media includes permanent and non-permanent, removable and non-removable media, and storage of information can be accomplished by any method or technology.
  • Information may be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory or other memory technology, Compact Disc Read Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
  • PRAM phase-change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • ROM read only memory
  • EEPROM Electrically Erasable Programmable Read Only Memory
  • Flash Memory or other memory technology
  • CD-ROM Compact Disc Read Only Memory
  • CD-ROM Compact Disc Read Only Memory
  • DVD Digital Versatile Disc
  • Magnetic tape cassettes magnetic tape magnetic disk storage or other magnetic storage devices or any other non-

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Abstract

一种红外图像传感器、红外图像处理方法及装置。所述红外图像传感器包括感光像素阵列，所述感光像素阵列包括至少两种的感光像素，不同类型的感光像素具有不同的感光能力。通过将感光像素阵列中的感光像素设计成具有不同的感光能力，从而使得感光像素对应的信噪比、测温精度和测温范围更加灵活多变，红外传感器在单次曝光过程中即可以兼顾较高的测温精度、较大的测温范围，并得到画质较高的红外图像。

Description

红外图像传感器、红外图像处理方法及装置 技术领域
本申请涉及红外图像技术领域，具体而言，涉及一种红外图像传感器、红外图像处理方法及装置。
背景技术
目前的红外传感器的感光像素都是均等感光，为了使红外传感可以具有不同的测温精度和测温范围，通常可以将红外传感器设置成不同的增益模式，用户在使用红外传感器的过程中，需通过切换红外传感器的模式实现不同的测温精度和测温范围。在测温精度高的模式下，可以得到较高画质的红外图像，但是测温范围较小，无法实现对高温对象进行测温。而在测温精度较低的模式下，可以得到较大的测温范围，以实现对高温对象测温，但是采集的红外图像画质很低，测温精度也很低。由于目前的红外传感器无法同时兼顾高测温精度、高测温范围和高观瞄画质，给用户的使用带来诸多不便。
发明内容
有鉴于此，本申请提供一种红外图像传感器、红外图像处理方法及装置。
根据本申请的第一方面，提供一种红外图像传感器，所述红外图像传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
根据本申请的第二方面，提供一种红外图像采集装置，所述红外图像采集装置包括上述第一方面提及的红外图像传感器。
根据本申请的第三方面，提供一种图像处理方法，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述方法包括：
获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
根据本申请的第四方面，提供一种红外图像处理方法，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述方法包括：
根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
基于所述至少两帧子图像得到目标图像。
根据本申请的第五方面，提供一种红外图像处理装置，用于处理红外图像，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置包括处理器、存储器、存储于所述存储器上可供所述处理器执行的计算机程序，所述处理器执行所述计算机程序时实现以下步骤：
获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
根据本申请的第六方面，提供一种红外图像处理装置，用于处理红外图像，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置包括处理器、存储器、存储于所述存储器上可供所述处理器执行的计算机程序，所述处理器执行所述计算机程序时实现以下步骤：
根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
基于所述至少两帧子图像得到目标图像。
根据本申请的第七方面，提供一种计算机可读存储介质，其上存储有计算机程序指令，当该指令被处理器执行时，可实现上述第三方面或第四方面提及红外图像处理方法。
应用本申请提供的方案，提供一种红外图像传感器，所述红外图像传感器包括感光像素阵列，所述感光像素阵列包括至少两种的感光像素，不同类型的感光像素具有不同的感光能力。通过将感光像素阵列中的感光像素设计成具有不同的感光能力，从而使得感光像素对应的信噪比、测温精度和测温范围更加灵活多变，红外传感器在单次曝光过程中即可以兼顾较高的测温精度、较大的测温范围和较高的画质，无需用户在使用过程中进行模式切换。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附 图获得其他的附图。
图1是本申请实施例的一种感光像素阵列的示意图。
图2是本申请实施例的一种感光像素阵列中不同类型的感光像素的分布情况示意图。
图3是本申请实施例的一种感光像素阵列中不同类型的感光像素的分布情况示意图。
图4是本申请实施例的一种感光像素阵列中子阵列的示意图。
图5是本申请实施例的另一种红外图像处理方法的流程图。
图6是本申请实施例的另一种红外图像处理方法的流程图。
图7是本申请实施例的一种红外图像处理装置的逻辑结构示意图。
图8是本申请实施例的另一种红外图像处理装置的逻辑结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
目前的红外传感器中各感光像素都是均等感光，即各感光像素的感光能力是一致的。为了实现红外传感器具备不同测温精度和不同测温范围，通常可以将红外传感器设置成不同的测温模式(不同测温模式下对感光像素接收到光信号转换成的电信号进行不同倍数的放大处理)，比如，目前的红外传感器通常具有高增益模式和低增益模式。在高增益模式下，红外传感器的测温精度高，信噪比高，采集的图像观瞄画质也更好更清晰，但是，测温范围却比较窄，比如，大多数红外传感器在高增益模式下的测温范围为-40～150℃，精度在±2℃左右。而在低增益模式下，红外传感器的测温范围广，但测温精度低，信噪比低，观瞄图像模糊不清晰，比如，大多数红外传感器在低增益模式下的测温范围为-40～550℃，精度在±5℃或更差。
由于在同一模式下，无法实现高测温精度、高测温范围以及高画质兼容，因此，用户在使用红外传感器测温时，当场景中出现高温物体(比如，250℃，超出高增益模式下的测温范围)，此时，如果用户要测量高温物体的温度则需要用户将红外传感器的模式切换为低增益模式，才能测量高温物体的温度，但是此模式下采集的红外图像的画面会很模糊，不方便用户观瞄，且测温精度也很低。如果用户想要更好的看清楚周围物体，则需要切换 至高增益模式，但是此模式下又会失去对超范围的高温物体的测量能力。目前的红外传感器无法兼顾测温精度、测温范围和画质，需要在使用过程切换模式，给用户的使用带来诸多不便。
基于此，本申请实施例提供了一种红外图像传感器，该红外图像传感器包括感光像素阵列，感光像素阵列包括至少两种类型的感光像素，不同类型的感光像素对应不同的感光能力，如图1所示，示出了本申请实施例提供的一种感光像素阵列，其包括两种类型的感光像素，即图中示出的N和L。感光像素可用于接收外界物体辐射的红外光，进而将接收到的红外光信号转换为电信号，并输出各像素对应的像素值，基于像素值可以确定各像素点对应的温度信息。由于不同类型的感光像素具有不同的感光能力，因而，针对同一强度的红外光信号，不同类型的感光像素感受到的光强度不一样，进而转化的电信号强度也不一样，由此，在单次曝光过程中则可以通过不同类型的感光像素采集得到对应于不同的信噪比、或不同的测温精度、或不同测温范围、或信噪比、测温精度、测温范围均不同的像素值，从而采集到的同一图像中可以包含不同测温精度、不同测温范围、不同信噪比的像素点，相比于各感光像素均等感光的红外传感器，本申请实施例提供的红外图像传感器的测温范围、测温精度和信噪比的设置更加灵活多变，在单次曝光过程中可以实现兼顾测温范围、测温精度和画质。
其中，感光像素的类型可以根据实际需求设置成两种、三种甚至更多种，不同类型的感光像素的数量可以相同，也可以不同。不同类型的感光像素之间的感光能力的差异也可以根据实际需求设置，不同感光像素对应的测温精度、测温范围也可以根据实际需求设置，对此，本申请实施例均不作限制。
当然，红外传感器除了包括上述感光像素阵列，还可以包括其他通用的用于实现红外成像和测温的元器件，在此不再展开描述。
通过在红外传感器的感光像素阵列设置多种类型的感光像素，不同类型的感光像素设置成不同的感光能力，使得红外传感器的测温范围、测温精度、信噪比的设置可以更加灵活多变，单次曝光过程中即可以兼顾测温范围、测温精度和画质，使用过程中无需用户进行模式切换，更加方便用户使用。
为了实现不同类型的感光像素具备不同的感光能力，在一些实施例中，可以通过改变感光像素的曝光时长以得到不同感光能力的感光像素。比如，可以控制不同类型的感光像素在红外传感器每次曝光过程中的曝光时长不同，从而使得每次曝光过程中，不同类型的感光像素接收到的红外光的量不同，以实现不同的感光能力。其中，曝光时长越长，感光像素的感光能力也越强。以图1所示的感光像素阵列为例，可以控制感光像素N在单次曝光过程中的曝光时长为0.2s，而感光像素L在单次曝光过程中的曝光时长为0.1s，以获取差异化的感光能力。
在一些实施例中，也可以通过改变感光像素自身的物理特性使得感光像素具备不同的感光能力。其中，物理特性可以是任一与感光像素对红外光的响应能力相关的特性。比如，在一些实施例中，物理特性可以是感光像素的面积、感光像素的材质或者感光像素的透光率等一种或者多种。比如，可以为不同类型的感光像素设置成不同的感光面积，使得每次曝光过程中，不同类型的感光像素接收到的红外光的量不同。当然，也可以针对不同类型的感光像素采用不同的材质，不同材质的感光像素对红外光的响应特性不一样。当然，也可以在不同类型的感光像素上设置对红外光具有不同透光率的滤光片，使得不同类型的感光像素接收到的红外光的量不一样，从形成差异化的感光能力。
由于不同类型的感光像素的感光能力不一样，因而在每次曝光过程中，不同类型的感光像素感受到的红外光强度也不一样，从而转换成的电信号的强度也不一样，进而可以为不同类型的感光像素设置不同的测温精度以及不同的测温范围。在一些实施例中，不同类型的感光像素可以对应不同的测温精度，或者不同类型的感光像素可以对应不同的测温范围，或者，不同类型的感光像素可以对应不同的测温精度以及测温范围。
在一些实施例中，感光阵列上的感光像素的感光能力越强，则其对应的测温精度越高，且其对应的测温范围越小。感光像素的感光能力越强，则同样的红外光到达该感光像素时，其感受到的光信号越强，转化后的电信号也越强，因而其测温精度可以越高，同时，由于其转化后的电信号越强，为了使其放大后的信号不会超过信号处理元件所能处理的信号强度，因而其放大倍数也有限，导致其测温范围也会相对较小。
红外传感器上的感光阵列中不同类型的感光像素的数量可以设置成一样，也可以设置成不一样，具体可以根据实际需求设置。由于红外传感器在用于对场景中的对象测温时，场景中对象的温度的分布范围不一样，有些温度范围内分布的对象多，较密集，有些温度范围内分布的对象少。对于分布对象较为密集的温度范围，其对应的感光像素应尽可能多一些(即对该温度范围具备测量能力的感光像素数量尽可能多)，以保证多数对象测温结果的准确性。而对于分布对象较少的温度范围，则该温度范围对应的感光像素可以适当少一些，也可以满足该温度范围的对象的测温需求。
所以，在一些实施例中，在设置不同类型的感光像素的数量时，可以基于每种类型的感光像素对应的测温精度和/或测温范围确定该种类型的感光像素的数量。
在一些实施例中，被测温对象的温度在某个测温范围内的分布越密集，则该测温范围对应的感光像素的数量越多，即对该测温范围具备测温能力的感光像素的数量越多。举个例子，假设感光阵列包括感光像素N和感光像素L两种类型的感光像素，感光像素N的测温范围为-40～150℃，感光像素L的测温范围为-40～550℃，而测温场景中的对象的温度大多分布在-40～150℃这一温度范围内，仅少数超出150℃，因而感光像素N的数量可以设置的多一些，感光像素L的数量可以少一些。
在一些实施例中，为了可以实现高测温精度、高测温范围以及高观瞄画质，感光像素阵列可以包括两种类型的感光像素：第一感光像素和第二感光像素，第一感光像素对应的测温精度低于第二感光像素对应的测温精度且第一感光像素对应的测温范围大于第二感光像素对应的测温范围，并且第一感光像素的数量少于第二感光像素的数量。其中，第一感光像素用于实现较高的测温精度，第二感光像素用于实现较大的测温范围。
举个例子，目前的红外传感器一般包括低增益模式和高增益模式，低增益模式下的测温范围为-40～550℃，精度在±5℃左右，而高增益模式的测温范围为-40～150℃，精度在±2℃左右，低增益模式可以实现高测温范围，而高增益模式可以实现高测温精度。为了实现红外传感器无需模式切换即可以兼顾高测温范围以及高测温精度，因而可以在红外传感器的感光像素阵列中设置两种类型的感光像素，其中，第一感光像素可以对齐低增益模式，其测温范围可以达到-40～550℃，精度在±-5℃左右，而第二感光像素可以对齐高增益模式，其测温范围可以达到-40～150℃，精度在±2℃左右，这样无需进行模式切换，既可以实现高测温范围，又可以实现高测温精度。同时，由于大多数对象的温度都分布在-40～150℃，仅少数对象的温度超出150℃，因而，第二感光像素的数量可以多于第一感光像素的数量。比如，在一些实施例中，第二感光像素的数量占比为75％，第一感光像素的数量占比为25％。
此外，目前红外传感器即便在高增益模式下，其测温精度也无法满足某些对象的测温需求，比如，无法满足人体测温需求。在一些实施例中，为了可以实现高测温精度同时还可以对特定温度范围的对象实现超高精度的测温，感光像素阵列可以包括两种类型的感光像素：第一感光像素和第二感光像素，第一感光像素对应的测温精度高于第二感光像素的测温精度且第一感光像素对应的测温范围小于第二感光像素的测温范围，并且第一感光像素的数量少于第二感光像素的数量。其中，第一感光像素用于实现对特定温度范围内的对象(比如，人体)进行超高精度的测温，第二感光像素用于实现对普通对象相对较高测温精度。
举个例子，虽然，目前的红外传感器在高增益模式下具有较高的测温精度，但对于某些测温对象来说该测温精度依然不够，比如，高增益模式下的测温精度为±2℃左右，但是对于人体测温来说，该精度还远远不够，其需要更高的测温精度，我们将这种需要超高测温精度的模式称为超高增益模式，该模式能够实现对特定温度范围内的对象进行超高精度的温度测量，以人体测温为例，其温度范围可以是30～45度，精度±0.5度。因而，可以设置两种类型的像素，第一感光像素对齐超高增益模式，第二感光像素可以对齐高增益模式，这样无需进行模式切换，即可以实现高测温精度，又可以实现对特定对象的超高精度测温。同时，由于大多数对象仅需高精度的温度测量，仅少数对象需要超高精度的温度测量，因而，第一感光像素的数量可以少于第二感光像素的数量。比如，在一些实施例中，第一感光像素的数量占比为25％，第二感光像素的数量占比为75％。
在一些实施例中，为了同时实现高测温范围、高测温精度、且对特定温度范围内的对象超高精度的测温，感光像素阵列可以包括三种类型的感光像素：第一感光像素、第二感光像素和第三感光像素，第一感光像素对应的测温精度低于第二感光像素的测温精度且第一感光像素对应的测温范围大于第二感光像素的测温范围，第三感光像素对应的测温精度高于第二感光像素且第三感光像素对应的测温范围小于第二感光像素的测温范围，第一感光像素的数量和第三感光像素的数量均少于所述第二感光像素的数量。其中，第一感光像素用于实现较高测温精度，第二感光像素用于实现较大的测温范围，第三感光像素用于实现对特定温度范围的对象进行超高精度的测温。
举个例子，为了同时实现高测温范围、高测温精度以及特定对象的超高精度测量，可以设置三种类型的感光像素，第一感光像素对齐低增益模式，可以实现高测温范围，第二感光像素对齐高增益模式，可以实现高测温精度、高观瞄画质，第三感光像素对齐超高增益模式，可以实现对特定温度范围的对象进行超高精度的测温。通过上述红外传感器，无需进行模式切换，即可以实现高测温范围、高测温精度和高观瞄画质，并且还可以实现对某些特定物体进行超高精度的测温。当然，由于测温范围和测温精度对应于高增益模式的对象数量的较多，因而，第二感光像素的数量可以多于第一感光像素和第三感光像素的数量。比如，在一些实施例中，第二感光像素的数量占比为50％，第一感光像素和第三感光像素的数量占比均为25％。
当然，由于感光像素阵列包括至少两种类型的感光像素，不同类型的感光像素的排列方式也会对测温精度以及图像的画质产生一定的影响。比如，同一类型的感光像素应尽可能在感光像素阵列中比较分散的排布(如图1所示)，而不应该是一种类型的感光像素集中在一片区域(如图2所示)，这样采集的红外图像中，每个对象对应的像素点的像素值都包括由不同类型的感光像素采集得到的像数值，从而可以采用合适的感光像素采集的像素值进一步测温，或者基于不同类型的感光像素得到画质较好的观瞄图像。
因而，在一些实施例中，当感光像素阵列包括上述第一感光像素和第二感光像素两种类型的感光像素，且第一感光像素的数量少于第二感光像素的数量时，每个第一感光像素可以分布在多个第二感光像素阵列之间，如图3所示，图中的L表示第一感光像素，N表示第二感光像素。在一些实施例中，当感光像素阵列包括第一感光像素、第二感光像素和第三感光像素阵列三种类型的感光像素，且第一感光像素和第三感光像素的数量少于第二感光像素时，则每个第一感光像素或每个第三感光像素可以分布在多个第二感光像素之间。
在一些实施例中，感光像素阵列中的至少两种类型的感光像素可以按照预设排列规则均匀分布或者随机分布。以感光像素阵列包括两种类型的感光像素(感光像素N和感光像素L)为例，两种类型的感光像素可以交替排布，也可以每四个感光像素N包围一个感光像素L、或者每两个感光像素N之后接一个感光像素L等，其中，具体的排布规则可以基 于不同类型的感光像素的数量和实际需求设置。当然，两种类型的感光像素也可以随机排布。只要尽可能保证一定范围的像素区域内包括该至少两种类型的感光像素即可。
在一些实施例中，为了确保不同类型的感光像素分布比较均匀，该感光像素阵列可划分成多个子阵列，每个子阵列中均包括该至少两种类型的感光像素。举个例子，如图4所示，假设有三种类型的感光像素(如图4中的N、L、H)，可以将感光像素阵列划分成多个矩形的子阵列，每个子阵列中都包括该三种类型的感光像素。其中，子阵列的大小可以基于实际需求设置，子阵列越小，说明不同类型的感光像素在感光阵列中分布越均匀。
在一些实施例中，如图4所示，每种类型的感光像素在每个子阵列中的数量可以一致。比如，假设有三种类型的感光像素，N、L、H，则每个子阵列中都包含N、L、H，且三种感光像素的数量都一致。当然，每个子阵列中三种类型的感光像素的数量也可以不一致，比如，可以有些子阵列中N多一些，有些子阵列中L多一些。
在一些实施例中，如图4所示，该至少两种类型的感光像素在每个子阵列中的排布方式一致。比如，假设有三种类型的感光像素，N、L、H，则每个子阵列中都包含N、L、H，且三种感光像素的排布方式都一致。
此外，本申请实施例还提供了一种红外图像采集装置，该红外图像采集装置包括上述实施例中描述的红外图像传感器。
当然，为了使得红外传感器的测温范围、测温精度可以更加灵活多变，在设计红外传感器时，感光像素阵列上的感光像素的感光能力可以不一致，不需要统一均等感光。针对该种红外传感器采集的红外图像，由于图像中包括不同类型的像素点，不同类型的像素点通过不同感光能力的感光像素采集得到，从而这些不同类型的像素点的测温精度、测温范围、信噪比也会不一样，因而，可以基于这些不同类型的像素点的特点更加准确的测量对象的温度。
基于此，本申请实施例提供了一种红外图像处理方法，该方法适用于对包括至少两种类型的像素点的红外图像进行处理，以确定红外图像中各图像区域对应的对象的温度。其中，不同类型的像素点的像素值通过不同感光能力的像素点采集得到。如图5所示，所述方法包括以下步骤：
S502、获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
S504、根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
由于红外图像中包括不同类型的像素点，不同类型的像素点的像素值可以通过不同感光能力的感光像素采集得到，而不同感光能力的感光像素可以对应不同的测温范围和/或测温精度。由于不同类型的像素点对应的测温精度、测温范围可以不一样，而红外图像中不同图像区域对应的对象对测温范围和测温精度的需求也不一样。因而，在确定红外图像中 目标图像区域对应的对象的温度时，可以先获取该目标图像区域内的不同类型的像素点的像素值，然后基于不同类型的像素点的特点以及其像素值综合确定目标图像区域对应的对象的温度。比如，可以选取其中测温结果更为准确的像素点确定该对象的温度，或者综合不同类型的像素点确定的温度得到该对象最终的温度。
当然，由于不同类型的像素点对应的测温精度、测温范围不一样，而红外图像中不同图像区域对应的对象对测温范围和测温精度的需求也不一样。因而，在利用上述至少两种类型的像素点确定目标图像区域对应的对象的温度时，为了测得的温度更加准确，可以先根据该至少两种类型的像素点的像素值从该至少两种类型的像素点中第一目标类型的像素点，然后利用第一目标类型的像素点的像素值确定目标图像区域对应的对象的温度。其中，第一目标类型的像素点对应的测温范围和测温精度更加符合目标图像区域对应的对象的需求，即利用第一目标类型的像素点可以更加准确地确定目标图像区域对应的对象的温度。
由于不同类型的像素点对应的测温范围不一样，在一些场景中，当基于某种类型的像素点确定的该对象的温度的饱和程度较高时，即根据该种类型的像素点确定的该对象的温度已经接近该种类型的像素点对应的测温范围的上限，那么利用该种类型的像素点确定的对象的温度很可能不准确，此时，应选择饱和程度更低的像素点确定该对象的温度。所以，在一些实施例中，在根据至少两种类型的像素点的像素值从该至少两种类型的像素点中确定第一目标类型的像素点时，可以根据该至少两种类型的像素点中的每种类型的像素点的像素值确定该对象的温度，并基于确定的温度以及每种类型的像素点的测温范围确定该种类型的像素点对应的饱和程度，基于该饱和程度从至少两种类型的像素点中确定第一目标类型的像素点。
举个例子，假设红外图像包括两种类型的像素点，像素点N和像素点L，像素点N对应的测温范围为-40～150℃，像素点L对应的测温范围为-40～200℃，假设根据像素点N的像素值确定对象A的温度为149℃，而根据像素点L的像素值确定对象A的温度为154℃，很明显，根据像素点N的像素值确定对象A的温度已接近饱和，即非常接近测温范围的上限，因此，根据像素点N确定的温度很可能不准确，此时应将像素点L作为第一目标类型的像素点，用于确定对象A的温度。
此外，由于不同类型的像素点对应的测温精度不一样，而不同的对象其所需的测温精度也不一样，因而，需尽可能选择测温精度符合被测对象测温精度需求的像素点用于确定被测对象的温度。所以，在一些实施例中，在根据至少两种类型的像素点的像素值从该至少两种类型的像素点中确定第一目标类型的像素点时，可以先根据该至少两种类型的像素点的像素值确定该对象的温度范围，并基于该对象的温度范围确定该对象的类型，然后根据该对象的类型和该至少两种类型的像素点对应测温精度从至少两种类型的像素点中确 定第一目标类型的像素点。
举个例子，假设红外图像包括两种类型的像素点，像素点N和像素点L，像素点N对应的测温精度为±0.5℃，像素点L对应的测温精度为±2℃，假设根据像素点N和像素点L确定对象A的温度范围为35-37℃，因而，基于该温度范围可以确定对象A很有可能是人体，因而可以根据人体测温对测温精度的要求应将像素点N作为第一目标类型的像素点，用于确定对象A的温度。
通过从不同类型的像素点中选择测温范围或者测温精度更加符合待测温对象的测温需求的像素点，用于确定待测温对象的温度，可以得到更加准确的测温结果，提升红外的测温精度。并且，对于同一场景中包含温度相差较大的多种对象，或者对测温精度要求不同的多种对象时，也无需切换红外传感器的模式来采集多帧红外图像以满足不同对象的测温需求，采集一帧红外图像即可以实现对不同对象的高精度测温。
当然，红外图像除了用于测量对象的温度，还可以用于观瞄，用于观瞄时，要求红外图像具有尽可能高的画质。由于不同类型的像素点由不同感光能力的感光像素采集，因而，不同类型的像素点对应的信噪比也不同，即由不同类型的像素点得到图像的清晰度不同。为了得到画质较好的图像，可以基于不同类型的像素点的特性对红外图像进行处理，以得到画质更加清晰的图像。比如，可以利用信噪比较高的像素点的像素值对信噪比较低的像素点的像素值进行修正，得到画质更好的图像，也可以对红外图像进行滤波处理，滤波过程中，可以基于各像素点的信噪比确定各像素点的权重，比如信噪比高的像素点权重可以适当大一些，其中，滤波处理可以包括各类保边滤波处理。当然，也可以基于不同类型的像素点的像素值融合得到高画质的观瞄图像。
在一些实施例中，可以根据红外图像中的至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到，然后基于该至少两帧子图像得到目标图像。由于不同类型的像素点的得到的子图像的画质、清晰度均不一样，因而可以对不同类型的像素点的得到的子图像进行融合，得到画质较高的目标图像。
由于不同类型的像素点的数量可能不一样，因而各类型的像素点构成的图像的像素尺寸也可能不一样，为了便于后续处理，在基于不同类型的像素点得到子图像时，可以提取出同一类型的像素点，并对这些像素点进行上采样处理，得到指定像素尺寸的子图像，便于后续对子图像进行处理。其中，子图像的像素尺寸可以根据实际需求设置，比如，可以和数量最多的类型的像素点构成的子图像的像素尺寸一致，也可以和红外图像的像素尺寸一致。
由于不同类型的像素点的数量可能不一样，因而在根据子图像得到目标图像时，可以根据像素点数量最多的类型的像素点构成的子图像作为指导，以对其他子图像进行处理。所以，在一些实施例中，在基于至少两帧子图像得到目标图像时，可以先从至少两帧子图 像中确定目标子图像，其中，目标子图像基于第二目标类型的像素点得到，第二目标类型为该红外图像中数量最多的像素点对应的类型，然后以目标子图像作为导向图，对其他子图像进行导向滤波处理，然后对导向滤波处理后的其他子图像和目标子图像进行融合，以得到目标图像。
在一些实施例中，为了得到效果更好的目标图像，在基于至少两帧子图像得到目标图像时，可以先对该至少两帧子图像进行金字塔分解，然后将金字塔分解后的该至少两帧子图像在对应层上进行融合，以得到目标图像。
在一些实施例中，最终得到的目标图像的像素尺寸可以与红外图像的像素尺寸一致。比如，可以将同一类型的像素点提取出来，然后上采样成与红外图像像素尺寸一致的子图像，并将子图像进行融合处理，得到目标图像。当然，也可以将同一类型的像素点提取出来，然后上采样成和数量最多的类型的像素点构成的子图像的像素尺寸一致的子图像，对子图像进行融合处理后，再上采样成和红外图像的像素尺寸一致的目标图像。
举个例子，假设红外图像包括三种类型的像素点，像素点N、像素点L、像素点H，三种类型的像素点的像素值由不同感光能力的感光像素采集，其中，像素点N具有较高的信噪比和较高的测温精度，像素点L具有更低的信噪比，但是具有较大的测温范围，像素点H具有超高的信噪比和超高的测温精度，可用于对特定温度范围的对象进行超高精度的测温(比如，人体测温)。像素点N的数量占比为50％，像素点H和像素点N的数量占比为25％，三种类型的像素点在图像中均匀分布。在获取到红外图像后，可以将图像中的像素点N提取出来，构成子图像N，然后将像素点L、像素点H分别提取出来，并上采样成与子图像N尺寸一致的子图像L和子图像H，然后与子图像N作为导向图，分别对子图像L和子图像H进行导向滤波，得到滤波后的子图像L和滤波后子图像H，然后可以将子图像N、子图像L和子图像H进行融合，融合后上采样成与红外图像尺寸一致的目标图像。
在一些实施例中，所述红外图像通过红外传感器采集得到，所述红外传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
在一些实施例中，所述不同的感光能力通过改变所述感光像素的曝光时长得到；和/或
所述不同的感光能力通过改变所述感光像素的物理特性得到。
在一些实施例中，所述物体理特性包括所述感光像素的面积、所述感光像素的材质和/或所述感光像素的透光率。
在一些实施例中，不同类型的感光像素对应不同的测温精度和/或测温范围。
在一些实施例中，所述感光像素的感光能力越强，所述测温精度越高，所述测温范围越小。
在一些实施例中，每种类型的感光像素的数量基于每种类型的感光像素对应的测温精度和/或测温范围确定。
在一些实施例中，被测温对象的温度在所述测温范围内的分布越密集，则所述测温范围对应的感光像素的数量越多。
在一些实施例中，所述感光像素阵列可划分成多个子阵列，每个子阵列中均包括所述至少两种类型的感光像素。
在一些实施例中，每种类型的感光像素在每个所述子阵列中的数量一致。
在一些实施例中，所述至少两种类型的感光像素在每个所述子阵列中的排布方式一致。
其中，红外图像传感器的具体结构和特点可以参考上述红外图像传感器中各实施例的描述，在此不再赘述。
当然，为了使得红外传感器的测温范围和测温精度可以更加灵活，在设计红外传感器时，感光像素阵列上的感光像素的感光能力可以不一致，不需要统一均等感光。针对该种红外传感器采集的红外图像，由于图像中包括不同类型的像素点，不同类型的像素点通过不同感光能力的感光像素采集得到，从而这些不同类型的像素点的信噪比也不一样、进而构成的图像的画质也会不一样，因而，可以利用高信噪比的像素点对低信噪比的像素点进行修正，得到画质更高的图像。从而，在获得较高的测温精度的同时，也可以兼顾红外图像的画质。
基于此，本申请实施例提供了一种红外图像的处理方法，该方法适用于对包括至少两种类型的像素点的红外图像进行处理，其中，不同类型的像素点的像素值通过不同感光能力的像素点采集得到。如图6所示，所述方法包括以下步骤：
S602、根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
S604、基于所述至少两帧子图像得到目标图像。
由于不同类型的像素点具有不同的测温精度和信噪比，因而基于不同类型的像素点得到的子图像的画质也不一样。因此，可以将红外图像中同一类型的像素点提取出来，以得到子图像，不同类型的像素点得到的子图像具有不同的信噪比和清晰度，进而，可以利用这些子图像中画质较高的子图像对画质较低的子图像进行修正，以得到画质较好的目标图像。
通过此种方式，在采用包括不同感光能力的感光像素的红外传感器采集红外图像时，在单次曝光过程中，既可以满足对不同对象的测温范围需求，实现高测温范围，同时也可以得到高画质的红外图像。用户无需切换模式，即可以实现高测温范围和高画质。
在一些实施例中，基于所述至少两帧子图像得到目标图像，包括：
从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素 点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
在一些实施例中，基于所述至少两帧子图像得到目标图像，包括：
对所述至少两帧子图像进行金字塔分解；
将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
在一些实施例中，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
相应的，本申请实施例提供了一种红外图像处理装置，如图7所示，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置70包括处理器71、存储器72、存储于所述存储器可供所述处理器执行的计算机程序，所述处理71器执行所述计算机程序时，可实现以下步骤：
获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
在一些实施例中，所述处理器用于根据所述目标图像区域内的所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度时，具体用于：
根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点，其中，利用所述第一目标类型的像素点确定的所述对象的温度的准确度高于利用其它类型的像素点确定的所述对象的温度的准确度；
根据所述第一目标类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
在一些实施例中，所述处理器用于根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点时，具体用于：
根据所述至少两种类型的像素点中的每种类型的像素点的像素值确定所述对象的温度；
基于所确定的温度与所述每种类型的像素点对应的测温范围确定每种类型的像素点对应的饱和程度；
基于所述饱和程度从所述至少两种类型的像素点中确定第一目标类型的像素点。
在一些实施例中，所述处理器用于根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点时，具体用于：
根据所述至少两种类型的像素点的像素值确定所述对象的温度范围；
基于所述温度范围确定所述对象的类型；
基于所述对象的类型和所述至少两种类型的像素点对应测温精度从所述至少两种类 型的像素点中确定所述第一目标类型的像素点。
在一些实施例中，所述处理器还用于：
根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
基于所述至少两帧子图像得到目标图像。
在一些实施例中，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
在一些实施例中，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
对所述至少两帧子图像进行金字塔分解；
将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
在一些实施例中，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
在一些实施例中，所述红外图像通过红外传感器采集得到，所述红外传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
在一些实施例中，所述不同的感光能力通过改变所述感光像素的曝光时长得到；和/或
所述不同的感光能力通过改变所述感光像素的物理特性得到。
在一些实施例中，所述物体理特性包括所述感光像素的面积、所述感光像素的材质和/或所述感光像素的透光率。
在一些实施例中，不同类型的感光像素对应不同的测温精度和/或测温范围。
在一些实施例中，所述感光像素的感光能力越强，所述测温精度越高，所述测温范围越小。
在一些实施例中，每种类型的感光像素的数量基于每种类型的感光像素对应的测温精度和/或测温范围确定。
在一些实施例中，被测温对象的温度在所述测温范围内的分布越密集，则所述测温范围对应的感光像素的数量越多。
在一些实施例中，所述感光像素阵列可划分成多个子阵列，每个子阵列中均包括所述 至少两种类型的感光像素。
在一些实施例中，每种类型的感光像素在每个所述子阵列中的数量一致。
在一些实施例中，所述至少两种类型的感光像素在每个所述子阵列中的排布方式一致。
此外，本申请实施例还提供另一种红外图像的处理装置，如图8所示，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置包括处理器81、存储器82、存储于所述存储器82可供所述处理器81执行的计算机程序，所述处理器81执行所述计算机程序时，可实现以下步骤：
根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
基于所述至少两帧子图像得到目标图像。
在一些实施例中，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
在一些实施例中，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
对所述至少两帧子图像进行金字塔分解；
将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
在一些实施例中，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
相应地，本说明书实施例还提供一种计算机存储介质，所述存储介质中存储有程序，所述程序被处理器执行时实现上述任一实施例中红外图像处理方法。
本说明书实施例可采用在一个或多个其中包含有程序代码的存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。计算机可用存储介质包括永久性和非永久性、可移动和非可移动媒体，可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括但不限于：相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。
对于装置实施例而言，由于其基本对应于方法实施例，所以相关之处参见方法实施例的部分说明即可。以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
以上对本发明实施例所提供的方法和装置进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (60)

  1. 一种红外图像传感器，其特征在于，所述红外图像传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
  2. 根据权利要求1所述的红外图像传感器，其特征在于，所述不同的感光能力通过改变所述感光像素的曝光时长得到；和/或
    所述不同的感光能力通过改变所述感光像素的物理特性得到。
  3. 根据权利要求2所述的红外图像传感器，其特征在于，所述物体理特性包括所述感光像素的面积、所述感光像素的材质和/或所述感光像素的透光率。
  4. 根据权利要求1-3任一项所述的红外图像传感器，其特征在于，不同类型的感光像素对应不同的测温精度和/或测温范围。
  5. 根据权利要求4所述的红外图像传感器，其特征在于，所述感光像素的感光能力越强，所述测温精度越高，所述测温范围越小。
  6. 根据权利要求4或5所述的红外图像传感器，其特征在于，每种类型的感光像素的数量基于每种类型的感光像素对应的测温精度和/或测温范围确定。
  7. 根据权利要求6所述的红外图像传感器，其特征在于，被测温对象的温度在所述测温范围内的分布越密集，则所述测温范围对应的感光像素的数量越多。
  8. 根据权利要求1所述的红外图像传感器，其特征在于，所述至少两种类型的感光像素包括第一感光像素和第二感光像素，所述第一感光像素对应的测温精度低于所述第二感光像素对应的测温精度且所述第一感光像素对应的测温范围大于所述第二感光像素对应的测温范围，所述第一感光像素的数量少于所述第二感光像素的数量。
  9. 根据权利要求1所述的红外图像传感器，其特征在于，所述至少两种类型的感光像素包括第一感光像素和第二感光像素，所述第一感光像素对应的测温精度高于所述第二感光像素对应的测温精度且所述第一感光像素对应的测温范围小于所述第二感光像素对应的测温范围，所述第一感光像素的数量少于所述第二感光像素的数量。
  10. 根据权利要求1所述的红外图像传感器，其特征在于，所述至少两种类型的感光像素包括第一感光像素、第二感光像素和第三感光像素，所述第一感光像素对应的测温精度低于所述第二感光像素对应的测温精度且所述第一感光像素对应的测温范围大于所述第二感光像素对应的测温范围，所述第三感光像素对应的测温精度高于所述第二感光像素对应的测温精度且所述第三感光像素对应的测温范围小于所述第二感光像素的测温范围，所述第一感光像素的数量和所述第三感光像素的数量均少于所述第二感光像素的数量。
  11. 根据权利要求8-10任一项所述的红外图像传感器，其特征在于，每个所述第一感光像素或每个所述第三感光像素分布在多个所述第二感光像素之间。
  12. 根据权利要求1-11任一项所述的红外图像传感器，其特征在于，所述至少两种类型的感光像素按照预设排列规则均匀分布或者随机分布。
  13. 根据权利要求1-11任一项所述红外图像传感器，其特征在于，所述感光像素阵列可划分成多个子阵列，每个子阵列中均包括所述至少两种类型的感光像素。
  14. 根据权利要求13所述红外图像传感器，其特征在于，每种类型的感光像素在每个所述子阵列中的数量一致。
  15. 根据权利要求13所述红外图像传感器，其特征在于，所述至少两种类型的感光像素在每个所述子阵列中的排布方式一致。
  16. 一种红外图像采集装置，其特征在于，所述红外图像采集装置包括如权利要求1-15任一项所述的红外图像传感器。
  17. 一种红外图像的处理方法，其特征在于，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述方法包括：
    获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
    根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
  18. 根据权利要求17所述的方法，其特征在于，根据所述目标图像区域内的所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度，包括：
    根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点，其中，利用所述第一目标类型的像素点确定的所述对象的温度的准确度高于利用其它类型的像素点确定的所述对象的温度的准确度；
    根据所述第一目标类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
  19. 根据权利要求18所述的方法，其特征在于，根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点，包括：
    根据所述至少两种类型的像素点中的每种类型的像素点的像素值确定所述对象的温度；
    基于所确定的温度与所述每种类型的像素点对应的测温范围确定每种类型的像素点对应的饱和程度；
    基于所述饱和程度从所述至少两种类型的像素点中确定第一目标类型的像素点。
  20. 根据权利要求18所述的方法，其特征在于，根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点，包括：
    根据所述至少两种类型的像素点的像素值确定所述对象的温度范围；
    基于所述温度范围确定所述对象的类型；
    基于所述对象的类型和所述至少两种类型的像素点对应测温精度从所述至少两种类 型的像素点中确定所述第一目标类型的像素点。
  21. 根据权利要求19所述的方法，其特征在于，所述方法还包括：
    根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
    基于所述至少两帧子图像得到目标图像。
  22. 根据权利要求21所述的方法，其特征在于，基于所述至少两帧子图像得到目标图像，包括：
    从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
    以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
    对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
  23. 根据权利要求21所述的方法，其特征在于，基于所述至少两帧子图像得到目标图像，包括：
    对所述至少两帧子图像进行金字塔分解；
    将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
  24. 根据权利要求21-23所述的方法，其特征在于，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
  25. 根据权利要求17所述的方法，其特征在于，所述红外图像通过红外传感器采集得到，所述红外传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
  26. 根据权利要求17所述的方法，其特征在于，所述不同的感光能力通过改变所述感光像素的曝光时长得到；和/或
    所述不同的感光能力通过改变所述感光像素的物理特性得到。
  27. 根据权利要求26所述的方法，其特征在于，所述物体理特性包括所述感光像素的面积、所述感光像素的材质和/或所述感光像素的透光率。
  28. 根据权利要求25-27任一项所述的方法，其特征在于，不同类型的感光像素对应不同的测温精度和/或测温范围。
  29. 根据权利要求28所述的方法，其特征在于，所述感光像素的感光能力越强，所述测温精度越高，所述测温范围越小。
  30. 根据权利要求28或29所述的方法，其特征在于，每种类型的感光像素的数量基于每种类型的感光像素对应的测温精度和/或测温范围确定。
  31. 根据权利要求30所述的方法，其特征在于，被测温对象的温度在所述测温范围 内的分布越密集，则所述测温范围对应的感光像素的数量越多。
  32. 根据权利要求25-31任一项所述方法，其特征在于，所述感光像素阵列可划分成多个子阵列，每个子阵列中均包括所述至少两种类型的感光像素。
  33. 根据权利要求32所述的方法，其特征在于，每种类型的感光像素在每个所述子阵列中的数量一致。
  34. 根据权利要求33所述的方法，其特征在于，所述至少两种类型的感光像素在每个所述子阵列中的排布方式一致。
  35. 一种红外图像的处理方法，其特征在于，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述方法包括：
    根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
    基于所述至少两帧子图像得到目标图像。
  36. 根据权利要求35所述的方法，其特征在于，基于所述至少两帧子图像得到目标图像，包括：
    从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
    以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
    对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
  37. 根据权利要求35所述的方法，其特征在于，基于所述至少两帧子图像得到目标图像，包括：
    对所述至少两帧子图像进行金字塔分解；
    将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
  38. 根据权利要求35-37任一项所述的方法，其特征在于，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
  39. 一种红外图像的处理装置，其特征在于，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置包括处理器、存储器、存储于所述存储器可供所述处理器执行的计算机程序，所述处理器执行所述计算机程序时，可实现以下步骤：
    获取所述红外图像的目标图像区域内的所述至少两种类型的像素点的像素值；
    根据所述目标图像区域内所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
  40. 根据权利要求39所述的装置，其特征在于，所述处理器用于根据所述目标图像 区域内的所述至少两种类型的像素点的像素值确定所述目标图像区域对应的对象的温度时，具体用于：
    根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点，其中，利用所述第一目标类型的像素点确定的所述对象的温度的准确度高于利用其它类型的像素点确定的所述对象的温度的准确度；
    根据所述第一目标类型的像素点的像素值确定所述目标图像区域对应的对象的温度。
  41. 根据权利要求40所述的装置，其特征在于，所述处理器用于根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点时，具体用于：
    根据所述至少两种类型的像素点中的每种类型的像素点的像素值确定所述对象的温度；
    基于所确定的温度与所述每种类型的像素点对应的测温范围确定每种类型的像素点对应的饱和程度；
    基于所述饱和程度从所述至少两种类型的像素点中确定第一目标类型的像素点。
  42. 根据权利要求40所述的装置，其特征在于，所述处理器用于根据所述至少两种类型的像素点的像素值从所述至少两种类型的像素点中确定第一目标类型的像素点时，具体用于：
    根据所述至少两种类型的像素点的像素值确定所述对象的温度范围；
    基于所述温度范围确定所述对象的类型；
    基于所述对象的类型和所述至少两种类型的像素点对应测温精度从所述至少两种类型的像素点中确定所述第一目标类型的像素点。
  43. 根据权利要求41所述的装置，其特征在于，所述处理器还用于：
    根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
    基于所述至少两帧子图像得到目标图像。
  44. 根据权利要求43所述的装置，其特征在于，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
    从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
    以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
    对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
  45. 根据权利要求43所述的装置，其特征在于，所述处理器用于基于所述至少两帧 子图像得到目标图像时，具体用于：
    对所述至少两帧子图像进行金字塔分解；
    将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
  46. 根据权利要求43-45任一项所述的装置，其特征在于，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
  47. 根据权利要求39所述的装置，其特征在于，所述红外图像通过红外传感器采集得到，所述红外传感器包括感光像素阵列，所述感光像素阵列包括至少两种类型的感光像素，其中，不同类型的感光像素对应不同的感光能力。
  48. 根据权利要求39所述的装置，其特征在于，所述不同的感光能力通过改变所述感光像素的曝光时长得到；和/或
    所述不同的感光能力通过改变所述感光像素的物理特性得到。
  49. 根据权利要求48所述的装置，其特征在于，所述物体理特性包括所述感光像素的面积、所述感光像素的材质和/或所述感光像素的透光率。
  50. 根据权利要求47-49任一项所述的装置，其特征在于，不同类型的感光像素对应不同的测温精度和/或测温范围。
  51. 根据权利要求50所述的装置，其特征在于，所述感光像素的感光能力越强，所述测温精度越高，所述测温范围越小。
  52. 根据权利要求50或51所述的装置，其特征在于，每种类型的感光像素的数量基于每种类型的感光像素对应的测温精度和/或测温范围确定。
  53. 根据权利要求52所述的装置，其特征在于，被测温对象的温度在所述测温范围内的分布越密集，则所述测温范围对应的感光像素的数量越多。
  54. 根据权利要求47-53任一项所述装置，其特征在于，所述感光像素阵列可划分成多个子阵列，每个子阵列中均包括所述至少两种类型的感光像素。
  55. 根据权利要求54所述的装置，其特征在于，每种类型的感光像素在每个所述子阵列中的数量一致。
  56. 根据权利要求55所述的装置，其特征在于，所述至少两种类型的感光像素在每个所述子阵列中的排布方式一致。
  57. 一种红外图像的处理装置，其特征在于，所述红外图像包括至少两种类型的像素点，不同类型的像素点的像素值通过不同感光能力的感光像素采集得到，所述装置包括处理器、存储器、存储于所述存储器可供所述处理器执行的计算机程序，所述处理器执行所述计算机程序时，可实现以下步骤：
    根据所述红外图像中的所述至少两种类型的像素点得到至少两帧子图像，其中，每帧所述子图像基于同一类型的像素点得到；
    基于所述至少两帧子图像得到目标图像。
  58. 根据权利要求57所述的装置，其特征在于，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
    从所述至少两帧子图像中确定目标子图像，所述目标子图像基于第二目标类型的像素点得到，所述第二目标类型为所述红外图像中数量最多的像素点对应的类型；
    以所述目标子图像作为导向图，对所述其他子图像进行导向滤波处理；
    对所述导向滤波处理后的其他子图像和所述目标子图像进行融合，以得到所述目标图像。
  59. 根据权利要求57所述的装置，其特征在于，所述处理器用于基于所述至少两帧子图像得到目标图像时，具体用于：
    对所述至少两帧子图像进行金字塔分解；
    将金字塔分解后的所述至少两帧子图像在对应层上进行融合，以得到所述目标图像。
  60. 根据权利要求57-59任一项所述的装置，其特征在于，所述目标图像的像素尺寸与所述红外图像的像素尺寸一致。
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Publication number Priority date Publication date Assignee Title
CN101577287A (zh) * 2008-05-09 2009-11-11 三星电子株式会社 多层图像传感器
CN102857708A (zh) * 2011-10-17 2013-01-02 北京瑞澜联合通信技术有限公司 图像传感器、摄像装置及图像数据生成方法
US10477173B1 (en) * 2018-05-23 2019-11-12 Microsoft Technology Licensing, Llc Camera with tunable filter and active illumination
CN111626100A (zh) * 2020-03-26 2020-09-04 北京迈格威科技有限公司 屏下指纹装置及显示模组

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Publication number Priority date Publication date Assignee Title
CN101577287A (zh) * 2008-05-09 2009-11-11 三星电子株式会社 多层图像传感器
CN102857708A (zh) * 2011-10-17 2013-01-02 北京瑞澜联合通信技术有限公司 图像传感器、摄像装置及图像数据生成方法
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