CN113727028A - Modular night vision imaging camera - Google Patents
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- 238000012545 processing Methods 0.000 claims abstract description 13
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- 239000011159 matrix material Substances 0.000 claims description 3
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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
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
Abstract
The invention discloses a modularized night vision imaging camera, which comprises a plurality of identical imaging modules, a central image processing unit and a synchronous control module, wherein each imaging module comprises a lens, an image sensor, a synchronous interface, a distortion correction module and an image output module, the imaging modules adopt a plurality of imaging modules for shooting, photons of each imaging module are converted into electric charges and are converted into digital signals, and the digital signals of each channel are added to obtain enhanced signals. The distortion correction module corrects the digital image signals in real time so as to eliminate image inconsistency caused by the difference of lens distortion among the imaging modules. The invention continuously improves the detection capability of the imaging camera by increasing the number of units, avoids the risk that the multiplication technology may cause the burning of the camera under stronger light, and breaks through the limit caused by photon noise in a multiplication type low-light-level shooting system.
Description
Technical Field
The invention belongs to the technical field of photoelectric imaging, and particularly relates to a modularized night vision imaging camera.
Background
The existing low-light night vision cameras are divided into an image enhancement type low-light night vision camera and a charge multiplication type low-light night vision camera. The image enhancement type low-light night vision camera multiplies photons collected by an optical system through a microchannel plate, and then couples the multiplied photons to an image sensor to realize the enhancement of light intensity signals. The charge multiplication type low-light night vision camera firstly converts light into charges and then completes the multiplication of the charges on an image sensor, thereby realizing the enhancement of signals.
The existing low-light night vision camera has some limitations in use, including that light is too strong and cannot work in the daytime, the existing low-light night vision camera needs to be combined with a conventional sensor of a visible light wave band for use, meanwhile, the weak light detection capability of the existing low-light night vision camera is limited, and the noise generated by photons is an important factor limiting the signal-to-noise ratio of a system under the condition of less photon number. For example, for N photons, the self-generated photon noise is sqr (N). As the number of photons approaches a single photon, the signal-to-noise ratio will tend to 1. In the case of multiplication-type micro-light photographing systems, the photographing limit is the photographing of a single photon. Furthermore, the application of multiplication techniques may also lead to a risk of burning out the camera under strong light.
Disclosure of Invention
Aiming at the problems faced by the existing low-light night vision camera technology, the invention discloses a modular night vision imaging camera which adopts a plurality of shooting units for shooting, converts photons of each shooting unit into electric charges and then into digital signals, and adds the digital signals of each shooting unit in a calculation mode to obtain enhanced signals.
The invention discloses a modularized night vision imaging camera, which comprises a plurality of identical imaging modules, a central image processing unit and a synchronous control module, wherein each imaging module is connected with the central image processing unit and the synchronous control module.
The imaging module comprises a lens, an image sensor, a synchronous interface, a distortion correction module and an image output module.
The image sensor is located on the focal plane of the lens, all the imaging modules are placed in parallel, and the axes of the lenses of all the imaging modules point to the same direction, so that the non-directional light rays emitted by the same target are received by the lens of each imaging module and are imaged on the focal plane of the lens. The image sensor at the focal plane converts the light received by the image sensor into electric charge and further converts the electric charge into a digital image signal, and the image sensor outputs the digital image signal to the distortion correction module from a data interface of the image sensor.
And a data interface of the image sensor is connected with a distortion correction module, and the distortion correction module is connected with an image output module. The distortion correction module is realized by a digital signal processor or a field programmable array, digital image signals acquired by the image sensor are corrected in real time by utilizing methods such as polynomial geometric correction and the like so as to eliminate the inconsistency of the acquired digital image signals caused by the difference of lens distortion among the imaging modules, and the distortion correction module sends the digital image signals after real-time correction to the image output module.
The image output module is used for packaging the digital image signals after real-time correction and sending the packaged images to the central image processing unit. The image output module is realized by a USB transmitter or an Ethernet transmitter.
The image sensor is connected with a synchronous interface, the synchronous interface is used for receiving a trigger signal or a line-field synchronous signal of the image sensor, the synchronous interfaces of all the imaging modules are connected with the synchronous control module and are uniformly controlled by the synchronous control module, and synchronous shooting of all the imaging modules is achieved.
The central image processing unit is realized by a field programmable array or a GPU processor and comprises an image registration unit, an image superposition module and an image data interface. The image registration unit is connected with the image output module of each imaging module, and is used for carrying out image registration on the digital image signals output by the image output module of each imaging module and outputting the registered result to the image superposition module, and the image superposition module is connected with the image data interface.
The image registration unit performs image registration calculation by using image processing methods such as a reference star matching method or a corner matching method, and acquires registration information of each imaging module by extracting image features of a digital image signal output by an image output module of each imaging module to complete image registration.
The reference star matching method is characterized in that the star images shot by the imaging modules are subjected to feature recognition matching with the reference star images in the star catalogue, and the registration information of the imaging modules is obtained and comprises the translation amount and the rotation amount of digital image signals output by the image output module of each imaging module.
The corner matching method comprises the steps of firstly extracting corner features of digital image signals output by each imaging module, extracting corners, then extracting descriptors from the extracted corners, describing the corners by using mathematical features such as local random two-dimensional features, and the like, and then judging the corresponding relation of the corners in different images through the descriptors corresponding to the corners, so that registration information of each imaging module is obtained, wherein the registration information comprises the translation amount and the rotation amount of the digital image signals output by the image output module of each imaging module.
The method comprises the following steps of extracting the characteristic of an angular point of a digital image signal output by each imaging module, and extracting the angular point, and specifically comprises the following steps:
the gray value of a pixel point with coordinates (x, y) of the digital image under an image plane coordinate system is I (x, y), and the gradient I of the gray value in the directions of the x axis and the y axis is calculatedxAnd IyAnd gradient product
And IxIyAnd calculating a matrix M, wherein the calculation formula is as follows:
wherein, the two-dimensional gaussian function w (x, y) represents a window function of the pixel point (x, y). And calculating a Harris response value R corresponding to each pixel point, wherein the calculation formula is as follows:
R＝det(M)-k(trace(M))2，
where k is a constant term. And setting a discrimination threshold t to obtain a pixel point corresponding to the R value larger than the threshold t, namely the extracted corner point.
The image superposition module translates and rotates the images output by the image registration unit to realize image alignment, and then performs addition calculation on each translated and rotated image to obtain a sum image after alignment, wherein the sum image is used as the output of the image superposition module.
The addition calculation is to add the images after the translation and the rotation according to the addition principle of random noise, for N unit images output by the image registration unit, if the signal intensity of each unit image is s, the readout noise of each unit image is r, after the addition calculation, the signal intensity of the sum image output by the image superposition module is N & lts & gt, and the corresponding total readout noise is
Image signal-to-noise ratio improvement over that before superposition
And (4) doubling.
The image superposition module is connected with the image output interface, and the image output interface converts the image after the addition calculation into image data for output. The image output interface is an HDMI interface, or a USB interface, or a network interface.
The invention has the beneficial effects that:
the detection capability of the weak light is related to the number of units of the system, so that the detection capability can be continuously improved by increasing the number of units. The invention does not require multiplication techniques and therefore there is no risk that multiplication may lead to burnout under stronger light. The invention is not limited by photon noise. In the case of a small number of photons, the noise generated by the photons itself is an important factor limiting the signal-to-noise ratio of the system. For example, for N photons, the self-generated photon noise is sqr (N). As the number of photons approaches a single photon, the signal-to-noise ratio will tend to 1. For multiplication-type micro-light photographing systems, the photographing limit is the photographing of a single photon. The computational imaging mode of the invention utilizes a plurality of units to increase the capability of acquiring photons, which is equivalent to increase the total number of photons, so the mode can break through the theoretical limit caused by photon noise in a multiplication type micro-light shooting system.
Drawings
Fig. 1 is a block diagram of the components of the modular night vision imaging camera of the present invention.
Detailed Description
For a better understanding of the present disclosure, an example is given here.
The invention discloses a modularized night vision imaging camera, which comprises a plurality of identical imaging modules, a central image processing unit and a synchronous control module, wherein each imaging module is connected with the central image processing unit and the synchronous control module, and the system structure is shown as the attached figure 1.
The imaging module comprises a lens, an image sensor, a synchronous interface, a distortion correction module and an image output module.
The image sensor is located on the focal plane of the lens, all the imaging modules are placed in parallel, and the axes of the lenses of all the imaging modules point to the same direction, so that the non-directional light rays emitted by the same target are received by the lens of each imaging module and are imaged on the focal plane of the lens. The image sensor at the focal plane converts the light received by the image sensor into electric charge and further converts the electric charge into a digital image signal, and the image sensor outputs the digital image signal to the distortion correction module from a data interface of the image sensor.
And a data interface of the image sensor is connected with a distortion correction module, and the distortion correction module is connected with an image output module. The distortion correction module is realized by a digital signal processor or a field programmable array, digital image signals acquired by the image sensor are corrected in real time by utilizing methods such as polynomial geometric correction and the like so as to eliminate the inconsistency of the acquired digital image signals caused by the difference of lens distortion among the imaging modules, and the distortion correction module sends the digital image signals after real-time correction to the image output module.
The image output module is used for packaging the digital image signals after real-time correction and sending the packaged images to the central image processing unit. The image output module is realized by a USB transmitter or an Ethernet transmitter.
The image sensor is connected with a synchronous interface, the synchronous interface is used for receiving a trigger signal or a line-field synchronous signal of the image sensor, the synchronous interfaces of all the imaging modules are connected with the synchronous control module and are uniformly controlled by the synchronous control module, and synchronous shooting of all the imaging modules is achieved.
The central image processing unit is realized by a field programmable array or a GPU processor and comprises an image registration unit, an image superposition module and an image data interface. The image registration unit is connected with the image output module of each imaging module, and is used for carrying out image registration on the digital image signals output by the image output module of each imaging module and outputting the registered result to the image superposition module, and the image superposition module is connected with the image data interface.
The image registration unit performs image registration calculation by using image processing methods such as a reference star matching method or a corner matching method, and acquires registration information of each imaging module by extracting image features of a digital image signal output by an image output module of each imaging module to complete image registration.
The reference star matching method is characterized in that the star images shot by the imaging modules are subjected to feature recognition matching with the reference star images in the star catalogue, and the registration information of the imaging modules is obtained and comprises the translation amount and the rotation amount of digital image signals output by the image output module of each imaging module.
The corner matching method comprises the steps of firstly extracting corner features of digital image signals output by each imaging module, extracting corners, then extracting descriptors from the extracted corners, describing the corners by using mathematical features such as local random two-dimensional features, and the like, and then judging the corresponding relation of the corners in different images through the descriptors corresponding to the corners, so that registration information of each imaging module is obtained, wherein the registration information comprises the translation amount and the rotation amount of the digital image signals output by the image output module of each imaging module.
The method comprises the following steps of extracting the characteristic of an angular point of a digital image signal output by each imaging module, and extracting the angular point, and specifically comprises the following steps:
the gray value of a pixel point with coordinates (x, y) of the digital image under an image plane coordinate system is I (x, y), and the gradient I of the gray value in the directions of the x axis and the y axis is calculatedxAnd IyAnd gradient product
And IxIyAnd calculating a matrix M, wherein the calculation formula is as follows:
wherein, the two-dimensional gaussian function w (x, y) represents a window function of the pixel point (x, y). And calculating a Harris response value R corresponding to each pixel point, wherein the calculation formula is as follows:
R＝det(M)-k(trace(M))2，
wherein k is a constant term, the value of k is set according to the characteristics of the digital image, and the value range of k is usually between 0.04 and 0.06. And setting a discrimination threshold t to obtain a pixel point corresponding to the R value larger than the threshold t, namely the extracted corner point.
The image superposition module translates and rotates the images output by the image registration unit to realize image alignment, and then performs addition calculation on each translated and rotated image to obtain a sum image after alignment, wherein the sum image is used as the output of the image superposition module.
The addition calculation is to add the images after the translation and the rotation according to the addition principle of random noise, for N unit images output by the image registration unit, if the signal intensity of each unit image is s, the readout noise of each unit image is r, after the addition calculation, the signal intensity of the sum image output by the image superposition module is N & lts & gt, and the corresponding total readout noise is
The signal-to-noise ratio of the target image of each unit is s/r, the signal-to-noise ratio of the image superposition module output and the image target is N s/r SQR (N) s/r, and the improvement of the image signal-to-noise ratio is realized.
The image superposition module is connected with the image output interface, and the image output interface converts the image after the addition calculation into image data for output. The image output interface is an HDMI interface, or a USB interface, or a network interface.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (6)
1. A modularized night vision imaging camera is characterized by comprising a plurality of identical imaging modules, a central image processing unit and a synchronous control module, wherein each imaging module is connected with the central image processing unit and the synchronous control module;
the imaging module comprises a lens, an image sensor, a synchronous interface, a distortion correction module and an image output module;
the image sensor is positioned on the focal plane of the lens, all the imaging modules are placed in parallel, and the lens axes of all the imaging modules point to the same direction so as to ensure that the non-directional light rays emitted by the same target are received by the lens of each imaging module and imaged on the focal plane of the lens; the image sensor at the focal plane converts the light received by the image sensor into electric charge and further converts the electric charge into a digital image signal, and the image sensor outputs the digital image signal to the distortion correction module from a data interface of the image sensor.
2. The modular night vision imaging camera of claim 1,
the data interface of the image sensor is connected with the distortion correction module, and the distortion correction module is connected with the image output module; the distortion correction module is realized by a digital signal processor or a field programmable array, digital image signals acquired by the image sensor are corrected in real time by utilizing a polynomial geometric correction method so as to eliminate the inconsistency of the acquired digital image signals caused by the difference of lens distortion among the imaging modules, and the digital image signals after real-time correction are sent to the image output module by the distortion correction module;
the image output module is used for packaging the digital image signals corrected in real time and sending the packaged images to the central image processing unit; the image output module is realized by a USB transmitter or an Ethernet transmitter;
the image sensor is connected with a synchronous interface, the synchronous interface is used for receiving a trigger signal or a line-field synchronous signal of the image sensor, and the synchronous interfaces of all the imaging modules are connected with the synchronous control module and are uniformly controlled by the synchronous control module, so that synchronous shooting of all the imaging modules is realized;
the central image processing unit is realized by a field programmable array or a GPU processor and comprises an image registration unit, an image superposition module and an image data interface; the image registration unit is connected with the image output module of each imaging module, is used for carrying out image registration on the digital image signals output by the image output module of each imaging module and outputting the registered result to the image superposition module, and the image superposition module is connected with the image data interface;
the image registration unit performs image registration calculation by using a reference star matching method or a corner matching method, and acquires registration information of each imaging module by extracting image features of a digital image signal output by an image output module of each imaging module;
the image superposition module translates and rotates the images output by the image registration unit to realize image alignment, and then performs addition calculation on each translated and rotated image to obtain a sum image after alignment, wherein the sum image is used as the output of the image superposition module;
the image superposition module is connected with the image output interface, and the image output interface converts the image subjected to the addition calculation into image data for output; the image output interface is an HDMI interface, or a USB interface, or a network interface.
3. The modular night vision imaging camera of claim 2,
the reference star matching method is characterized in that the star images shot by the imaging modules are subjected to feature recognition matching with the reference star images in the star catalogue, and the registration information of the imaging modules is obtained and comprises the translation amount and the rotation amount of digital image signals output by the image output module of each imaging module.
4. The modular night vision imaging camera of claim 2,
the corner matching method comprises the steps of firstly extracting the feature of a digital image signal output by each imaging module, extracting corners, then extracting descriptors from the extracted corners, describing the corners by using local random two-dimensional features, and then judging the corresponding relation of the corners in different images by the descriptors corresponding to the corners, so as to obtain the registration information of each imaging module, including the translation amount and the rotation amount of the digital image signal output by the image output module of each imaging module.
5. The modular night vision imaging camera of claim 4,
the method comprises the following steps of extracting the characteristic of an angular point of a digital image signal output by each imaging module, and extracting the angular point, and specifically comprises the following steps:
the gray value of a pixel point with coordinates (x, y) of the digital image under an image plane coordinate system is I (x, y), and the gradient I of the gray value in the directions of the x axis and the y axis is calculatedxAnd IyAnd gradient product
And IxIyAnd calculating a matrix M, wherein the calculation formula is as follows:
wherein, the two-dimensional Gaussian function w (x, y) represents a window function of the pixel point (x, y); and calculating a Harris response value R corresponding to each pixel point, wherein the calculation formula is as follows:
R＝det(M)-k(trace(M))2，
wherein k is a constant term; and setting a discrimination threshold t to obtain a pixel point corresponding to the R value larger than the threshold t, namely the extracted corner point.
6. The modular night vision imaging camera of claim 2,
the addition calculation is to add the images after the translation and the rotation according to the addition principle of random noise, for N unit images output by the image registration unit, if the signal intensity of each unit image is s, the readout noise of each unit image is r, after the addition calculation, the signal intensity of the sum image output by the image superposition module is N & lts & gt, and the corresponding total readout noise is
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