Image processing method based on germanium-silicon photoelectric detector array high dynamic acquisition

Abstract

The invention relates to the technical field of photoelectric detection and image processing, in particular to an image processing method based on high-dynamic acquisition of a germanium-silicon photoelectric detector array, which comprises the following steps of: S1, building an n * t germanium-silicon photoelectric detector array, converting an optical signal into a current signal by a detector unit, and amplifying the current signal into a voltage signal by a trans-impedance amplifier; s2, digitalizing the voltage signal through a high-speed analog-to-digital converter; s3, carrying out 1-1024 times of customizable global synchronous repeated sampling, and carrying out pixel-by-pixel superposition to generate a plurality of groups of fusion data; and S4, selecting fusion data corresponding to repeated sampling times according to the exposure condition of the original image. Through sampling frequency custom and data superposition design, flexible expansion of a detection dynamic range is realized, noise accumulation of a weak light scene is avoided, dark part details are restored, bright part saturation of a strong light scene is prevented, bright part details are reserved, and the detection accuracy is improved. The problems of overexposure, underexposure and poor sampling strategy adaptability caused by insufficient dynamic range of a traditional photoelectric detector are solved.

Description

Technical Field

[0001] This invention belongs to the field of photoelectric detection and image processing technology, and particularly relates to an image processing method based on high dynamic range acquisition of germanium-silicon photodetector array. Background Technology

[0002] Traditional germanium-silicon photodetectors are mostly single-detection units with limited spectral response ranges and can only detect specific wavelengths, making it difficult to meet the multi-band signal acquisition requirements in wide-spectral scenarios. Even though some wide-spectral improvement schemes have extended the response range through structural design, they have not addressed dynamic range optimization for array applications. Furthermore, in the practical application of large-scale germanium-silicon photodetector arrays, the signal preprocessing and sampling strategies of existing arrays are fixed, resulting in limited dynamic range. Due to physical limitations, they cannot cover the drastic changes in optical power in real-world scenarios. They are prone to overexposure when facing strong light signals and underexposure when facing weak light signals, leading to signal distortion or even device damage.

[0003] While high dynamic range technology attempts to improve the above problems, it mostly generates multiple frames of images by fixing exposure parameters and then fuses them. It relies on preset exposure strategies and cannot flexibly adapt to fluctuations in light power. In addition, although some solutions introduce germanium-silicon photodetectors to improve accuracy, they focus on optimizing detection stability and do not design dynamic adaptation mechanisms for image overexposure and underexposure problems. Summary of the Invention

[0004] In view of this, the present invention aims to provide an image processing method based on high dynamic range acquisition of germanium-silicon photodetector array, in order to solve the problems of traditional photodetectors being prone to overexposure or underexposure during the detection process due to insufficient dynamic range, resulting in image signal distortion, device damage, and the inability of image processing to flexibly adapt the sampling strategy according to the actual situation of the light signal.

[0005] To achieve the above objectives, the technical solution created by this invention is implemented as follows: An image processing method based on high dynamic range acquisition using a germanium-silicon photodetector array includes the following steps: S1. Construct an n×t germanium-silicon photodetector array, where n is the number of array columns and t is the number of array rows. Each germanium-silicon photodetector unit in the array serves as an independent pixel, used to receive the target light signal and convert it into an initial current signal. Connect an external transimpedance amplifier to each germanium-silicon photodetector unit to convert the initial current signal into a voltage signal and linearly amplify the voltage signal. S2. Connect a high-speed analog-to-digital converter to the output of each transimpedance amplifier. The high-speed analog-to-digital converter samples, holds, quantizes, and encodes the amplified voltage signal to obtain a binary discrete digital signal. S3. Perform global synchronous sampling on all the pixels to obtain a first set of binary discrete data arranged in pixel order; repeatedly sample the same target light signal using the same global synchronous sampling method to obtain multiple sets of binary discrete data; superimpose the multiple sets of binary discrete data one by one according to the pixels to generate fused data; wherein, the number of repeated samplings can be customized within the range of 1 to 1024 times. S4. Select the fusion data with the corresponding number of repeated samplings based on the exposure of the original image: if the original image is underexposed, select the fusion data with fewer repeated samplings; if the original image is overexposed, select the fusion data with more repeated samplings. The final output image has an exposure that meets the preset standard and has complete brightness and darkness details.

[0006] Furthermore, the amplification factor of the transimpedance amplifier is dynamically adjusted according to the intensity of the initial current signal. When the target optical signal is weak, the amplification factor is increased, and when the target optical signal is strong, the amplification factor is decreased.

[0007] Furthermore, the sampling rate of the high-speed analog-to-digital converter is matched with the optical signal response rate of the germanium-silicon photodetector unit to achieve real-time digital conversion of the target optical signal.

[0008] Furthermore, in step S3, the first group of binary discrete data arranged in pixel order is denoted as {x}. ij}, where i represents the row number of the pixel, j represents the column number of the pixel, and x ij This represents the sampled data of the pixel in the i-th row and j-th column, where the value of i is in the range of 1 ≤ i ≤ t, and the value of j is in the range of 1 ≤ j ≤ n.

[0009] Furthermore, in step S3, the second set of binary discrete data obtained by repeated sampling is denoted as {y}. ij}, where y ij Let represent the sampled data of the pixel in the i-th row and j-th column, where i ranges from 1 to i to t, and j ranges from 1 to j to n; the fused data after superimposing the two sets of data is {x}. ij +y ij}

[0010] Furthermore, in step S4, the number of repeated samplings is determined based on the exposure of the original image corresponding to the power of the target light signal: when the power of the target light signal is high, the original image is overexposed, and fewer repeated samplings are selected; when the power of the target light signal is low, the original image is underexposed, and more repeated samplings are selected.

[0011] Furthermore, in step S4, the exposure status of the original image is determined by calculating the average brightness value of the original image. When the average brightness value is lower than a preset brightness threshold, it is determined to be underexposed; when the average brightness value is higher than the preset brightness threshold, it is determined to be overexposed.

[0012] Furthermore, the number of repeated samplings is an integer power of 2.

[0013] Compared with the prior art, the present invention can achieve the following beneficial effects: By constructing an n×t germanium-silicon photodetector array and configuring a transimpedance amplifier for each detector unit to achieve electrical signal conversion and amplification, combined with a high-speed analog-to-digital converter to complete signal digitization, and then forming multiple sets of fused data through 1 to 1024 customizable global synchronous repeated sampling and pixel-by-pixel data superposition, the fused data with the corresponding number of samplings is finally selected according to the exposure of the original image. This achieves a custom expansion of the detection dynamic range. It can avoid noise accumulation and restore dark details in low-light scenes by sampling fewer times, and absorb excess signal energy and prevent bright saturation in strong light scenes by sampling multiple times. At the same time, it achieves flexible adaptation of sampling strategy to the actual situation of light signal, solving the problems of traditional photodetectors, which are prone to overexposure or underexposure during detection due to insufficient dynamic range, resulting in image signal distortion, device damage, and the inability of image processing to flexibly adapt the sampling strategy according to the actual situation of light signal. Attached Figure Description

[0014] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 A flowchart of an image processing method based on high dynamic range acquisition of a germanium-silicon photodetector array, provided for an embodiment of the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and do not constitute a limitation thereof. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the invention. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, some operations related to the invention are not shown or described in the specification. This is to avoid obscuring the core parts of the invention with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined to form various implementations. Furthermore, the order of the steps or actions in the method description can be changed or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various orders in the specification and drawings are merely for the clear description of a particular embodiment and do not imply a mandatory order, unless otherwise stated that a particular order must be followed.

[0017] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0018] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0019] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] like Figure 1 As shown, this embodiment provides an image processing method based on high dynamic range acquisition using a germanium-silicon photodetector array, including the following steps: S1. Construct an n×t germanium-silicon photodetector array, where n is the number of array columns and t is the number of array rows. Each germanium-silicon photodetector unit in the array is used as an independent pixel to receive the target light signal and convert it into an initial current signal. Connect an external transimpedance amplifier to each germanium-silicon photodetector unit to convert the initial current signal into a voltage signal and then linearly amplify the voltage signal.

[0021] Furthermore, the amplification factor of the transimpedance amplifier is dynamically adjusted according to the intensity of the initial current signal. When the target optical signal is weak, the amplification factor is increased, and when the target optical signal is strong, the amplification factor is decreased.

[0022] When the target optical signal power is high (strong light scenario), the initial current signal strength output by the germanium-silicon photodetector unit is large. In this case, the amplification factor of the transimpedance amplifier is set to a low value to avoid the amplified voltage signal exceeding the input range of the high-speed analog-to-digital converter, which would cause signal saturation. When the target optical signal power is low (weak light scenario), the initial current signal output by the detector unit is weak. In this case, the amplification factor of the transimpedance amplifier is set to a high value. Through linear amplification, the weak voltage signal reaches the effective acquisition threshold of the high-speed analog-to-digital converter, ensuring that the signal can be accurately quantized and encoded.

[0023] Meanwhile, the bandwidth of the transimpedance amplifier is matched with the optical signal response rate of the germanium-silicon photodetector unit to avoid signal distortion due to insufficient bandwidth, and to ensure that the amplified voltage signal completely retains the original characteristics of the target optical signal, providing a reliable signal foundation for subsequent digital conversion and data fusion.

[0024] S2. Connect a high-speed analog-to-digital converter to the output of each transimpedance amplifier. The high-speed analog-to-digital converter samples, holds, quantizes, and encodes the amplified voltage signal to obtain a binary discrete digital signal.

[0025] Furthermore, the sampling rate of the high-speed analog-to-digital converter is matched with the optical signal response rate of the germanium-silicon photodetector unit to achieve real-time digital conversion of the target optical signal.

[0026] The response rate of a germanium-silicon photodetector unit to a target optical signal is determined by its material properties and structural design, with the corresponding equivalent bandwidth of the target optical signal being the reciprocal of the response time. To ensure real-time capture of the dynamic changes in the target optical signal, the sampling rate of the high-speed analog-to-digital converter (ADC) should be no less than twice the equivalent bandwidth of the target optical signal, and in practical applications, it can preferably be set to 3 to 5 times the equivalent bandwidth of the target optical signal. This matching design avoids both the loss of high-frequency components and waveform distortion of the optical signal due to excessively low sampling rates, and the waste of hardware resources caused by excessively pursuing high sampling rates, ensuring that sampling efficiency and data accuracy are balanced while achieving real-time digital conversion.

[0027] S3. Perform global synchronous sampling on all pixels to obtain the first set of binary discrete data arranged in pixel order; repeatedly sample the same target light signal using the same global synchronous sampling method to obtain multiple sets of binary discrete data; superimpose the multiple sets of binary discrete data pixel by pixel to generate fused data; the number of repeated samplings can be customized within the range of 1 to 1024 times.

[0028] Furthermore, in step S3, the first group of binary discrete data arranged in pixel order is denoted as {x}. ij}, where i represents the row number of the pixel, j represents the column number of the pixel, and x ij Let represent the sampled data of the pixel in the i-th row and j-th column, where i is in the range of 1 ≤ i ≤ t and j is in the range of 1 ≤ j ≤ n.

[0029] Furthermore, in step S3, the second set of binary discrete data obtained by repeated sampling is denoted as {y}. ij}, where y ij Let represent the sampled data of the pixel in the i-th row and j-th column, where i ranges from 1 to 1 and j ranges from 1 to 1 and n respectively; the fused data after superimposing the two sets of data is {x}. ij +y ij}

[0030] Specifically, the first group of binary discrete data arranged in row-column order can be represented as {x 11 x 12 x 13 …x 1n …x 21 x 22 …x tn}, where each data item is uniformly represented by {x ijIn summary, 1 ≤ i ≤ t, 1 ≤ j ≤ n, where i corresponds to the row number of the pixel, j corresponds to the column number of the pixel, and x ij This represents the sampled data of the pixel in the i-th row and j-th column. The second set of binary discrete data obtained by repeated sampling is arranged in the same row-column order as {y}. 11 y 12 y 13 …y 1n …y 21 y 22 …y tn}, all data items are uniformly represented by {y ij In summary, where 1≤i≤t, 1≤j≤n, and y ij With x ij The row and column correspondences are completely consistent. When the two sets of data are superimposed one by one according to their corresponding pixels, the principle of "adding data in the same row and column" is followed, and the generated fused data is {x 11 +y 11 x 12 +y 12 x 13 +y 13 …x 1n +y 1n …x 21 +y 21 x 22 +y 22 …x tn +y tn All merged data items are uniformly represented by {x}. ij +y ij In summary, this precise overlay logic of "adding data in the same row and column" ensures that each set of repeatedly sampled data is perfectly aligned with the first set of data in terms of pixel position, avoiding signal misalignment caused by the mixing and overlay of pixel data from different rows and columns. For scenarios where the number of repeated samples is an integer power of 2 (such as 4, 8, 16, 32... up to 1024 times). Especially when the number of repeated samplings is an integer power of 2 (such as 4, 8, 16, 32... up to 1024 times), multiple sets of data obtained from subsequent samplings can be superimposed and fused sequentially according to the same "row-column" order and alignment principle. This superposition method not only adapts to the core design of custom sampling numbers, but also enhances the identifiability of weak light signals through the accumulation of multiple sets of data, while avoiding saturation of strong light signals due to excessive superposition. This effectively solves the signal distortion problem under different light intensity environments and improves the accuracy and reliability of detection data. At the same time, by superimposing data in integer powers of 2, the detection dynamic range can be accurately expanded, and the superposition operation logic of binary discrete data in the data processing process can be simplified, reducing the operation delay. This ensures that the optimal sampling number can be quickly matched under different light intensity scenarios (weak light to strong light), efficiently realizing the restoration of dark details in underexposed images and the preservation of bright details in overexposed images.

[0031] Furthermore, in step S3, after superimposing multiple sets of binary discrete data, the value of the fused data increases with the number of samplings, so as to cover a wider range of target optical signal power.

[0032] By incorporating a design that adjusts the number of repeated samplings as needed, when the target light signal power is low, increasing the number of samplings gradually accumulates and increases the value of the fused data, amplifying signals that were originally too weak to be detected to the effective detection range and avoiding underexposure. When the target light signal power is high, reducing the number of samplings controls the value of the fused data within a reasonable range, preventing the signal from becoming saturated and overexposed due to excessive superposition. This linkage of "number of samplings adjustment and value adaptation" allows the detection system to flexibly cover a wide power range from weak to strong light, breaking the limitations of the signal adaptation range restricted by the traditional fixed sampling mode, and significantly improving the system's adaptability and detection flexibility in complex light intensity environments.

[0033] S4. Select the fusion data with the corresponding number of repeated samplings based on the exposure of the original image: if the original image is underexposed, select the fusion data with fewer repeated samplings; if the original image is overexposed, select the fusion data with more repeated samplings. The final output image has an exposure that meets the preset standard and has complete brightness and darkness details.

[0034] Furthermore, in step S4, the exposure of the original image is determined by calculating the average brightness value of the original image. When the average brightness value is lower than the preset brightness threshold, it is determined to be underexposed; when the average brightness value is higher than the preset brightness threshold, it is determined to be overexposed.

[0035] Specifically, the average brightness value of the original image is calculated by traversing the grayscale values ​​of all pixels corresponding to the germanium-silicon photodetector array. The exposure status of the original image is determined by calculating the average brightness value. In this embodiment, the preset brightness threshold can be 128 within the grayscale value range of 0-255 (which can be adjusted according to the actual application scenario). When the average brightness value is lower than 128, it is determined that the original image is underexposed. At this time, the fusion data corresponding to 1 or 2 repeated samplings is selected to improve the overall brightness of the image while avoiding noise accumulation caused by excessive amplification of weak light signals, and accurately restores the details in the dark areas. When the average brightness value is higher than 128, it is determined that the original image is overexposed. At this time, the fusion data corresponding to 64, 128, or 1024 repeated samplings is selected. By superimposing multiple sets of data, the excess energy of strong light signals is absorbed, avoiding saturation distortion in bright areas and effectively restoring the details in bright areas. When the average brightness value is equal to 128, it is determined that the exposure is appropriate. The fusion data corresponding to 8, 16, or 32 repeated samplings is selected to directly output an image with balanced exposure, balanced brightness and darkness levels, and complete details, which meets the human eye's perception needs of real scenes.

[0036] The above technical solution constructs an n×t germanium-silicon photodetector array and equips each detector unit with a transimpedance amplifier to achieve electrical signal conversion and amplification. Combined with a high-speed analog-to-digital converter, the signal is digitized. Then, through 1 to 1024 customizable global synchronous repeated sampling and pixel-by-pixel data superposition, multiple sets of fused data are formed. Finally, the fused data with the corresponding number of sampling times is selected according to the exposure of the original image, realizing the custom expansion of the detection dynamic range. It can avoid noise accumulation and restore dark details in low-light scenes by sampling fewer times, and absorb excess signal energy and prevent bright saturation in strong light scenes by sampling multiple times. At the same time, it achieves flexible adaptation of the sampling strategy to the actual situation of the light signal. It solves the problems of traditional photodetectors, which are prone to overexposure or underexposure during detection due to insufficient dynamic range, resulting in image signal distortion, device damage, and the inability of image processing to flexibly adapt the sampling strategy according to the actual situation of the light signal.

[0037] Furthermore, in step S4, the number of repeated samplings is determined based on the exposure of the original image corresponding to the power of the target light signal: when the power of the target light signal is high, the original image is overexposed, and fewer repeated samplings are selected; when the power of the target light signal is low, the original image is underexposed, and more repeated samplings are selected.

[0038] By adjusting the number of repeated samplings as needed, combined with the logic of precisely superimposing multiple sets of data in the same row and column, this design avoids overexposure distortion caused by excessive data superposition leading to signal values ​​exceeding the effective range when the target light signal power is high (strong light scene), allowing for the acquisition of a clear and stable signal with only a small number of samples. Conversely, when the target light signal power is low (weak light scene), the superposition of multiple sets of data accumulates signal strength, compensating for the weakness and susceptibility to noise interference of a single sampled signal, and preventing signal loss due to underexposure. Ultimately, this achieves adaptive adaptation to target light signals of different power, effectively overcoming the bottleneck of limited dynamic range under traditional fixed sampling strategies, ensuring accurate and reliable fused data output under various light intensity environments, and meeting the requirements of high-precision detection.

[0039] In some embodiments, the spectral response range of each germanium-silicon photodetector unit in the germanium-silicon photodetector array is consistent to ensure consistent response to the same target optical signal. This consistency design, combined with global synchronous sampling and precise row-column superposition logic, ensures that the response data of the same target optical signal at different pixels is comparable and uniform. The fused data after superposition can truly restore the spatial distribution characteristics of the target optical signal, without signal distortion or artifacts caused by abnormal response of local units, further improving the reliability and accuracy of the detection data.

[0040] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0041] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. An image processing method based on high dynamic range acquisition of a germanium-silicon photodetector array, characterized in that, Includes the following steps: S1. Construct an n×t germanium-silicon photodetector array, where n is the number of array columns and t is the number of array rows. Each germanium-silicon photodetector unit in the array serves as an independent pixel, used to receive the target light signal and convert it into an initial current signal. Connect an external transimpedance amplifier to each germanium-silicon photodetector unit to convert the initial current signal into a voltage signal and linearly amplify the voltage signal. S2. Connect a high-speed analog-to-digital converter to the output of each transimpedance amplifier. The high-speed analog-to-digital converter samples, holds, quantizes, and encodes the amplified voltage signal to obtain a binary discrete digital signal. S3. Perform global synchronous sampling on all the pixels to obtain a first set of binary discrete data arranged in pixel order; repeatedly sample the same target light signal using the same global synchronous sampling method to obtain multiple sets of binary discrete data; superimpose the multiple sets of binary discrete data one by one according to the pixels to generate fused data; wherein, the number of repeated samplings can be customized within the range of 1 to 1024 times. S4. Select the fusion data with the corresponding number of repeated samplings based on the exposure of the original image: if the original image is underexposed, select the fusion data with fewer repeated samplings; if the original image is overexposed, select the fusion data with more repeated samplings. The final output image has an exposure that meets the preset standard and has complete brightness and darkness details.

2. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: The amplification factor of the transimpedance amplifier is dynamically adjusted according to the intensity of the initial current signal. When the target optical signal is weak, the amplification factor is increased, and when the target optical signal is strong, the amplification factor is decreased.

3. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: The sampling rate of the high-speed analog-to-digital converter is matched with the optical signal response rate of the germanium-silicon photodetector unit to achieve real-time digital conversion of the target optical signal.

4. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: In step S3, the first group of binary discrete data arranged in pixel order is denoted as {x}. ij }, where i represents the row number of the pixel, j represents the column number of the pixel, and x ij This represents the sampled data of the pixel in the i-th row and j-th column, where the value of i is in the range of 1 ≤ i ≤ t, and the value of j is in the range of 1 ≤ j ≤ n.

5. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 4, characterized in that: In step S3, the second set of binary discrete data obtained by repeated sampling is denoted as {y}. ij }, where y ij Let represent the sampled data of the pixel in the i-th row and j-th column, where i ranges from 1 to i to t, and j ranges from 1 to j to n; the fused data after superimposing the two sets of data is {x}. ij +y ij } 6. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: In step S4, the number of repeated samplings is determined based on the exposure of the original image corresponding to the power of the target light signal: when the power of the target light signal is high, the original image is overexposed, so fewer repeated samplings are selected; when the power of the target light signal is low, the original image is underexposed, so more repeated samplings are selected.

7. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: In step S4, the exposure of the original image is determined by calculating the average brightness value of the original image. When the average brightness value is lower than the preset brightness threshold, it is determined to be underexposed; when the average brightness value is higher than the preset brightness threshold, it is determined to be overexposed.

8. The image processing method based on high dynamic range acquisition of germanium-silicon photodetector array according to claim 1, characterized in that: The number of repeated samplings is an integer power of 2.

Images