KR20230101974A - integrated image providing device for micro-unmanned aerial vehicles - Google Patents

Abstract

The present invention relates to an integrated image providing device for a subminiature unmanned aerial vehicle and, more specifically, to an integrated image providing device for a subminiature unmanned aerial vehicle which receives EO camera images and IR camera images captured from the subminiature unmanned aerial vehicle and provides image data as a single integrated image. To integrate IR (infrared) camera video data and EO (electro-optical) camera video data on a single screen, a plurality of main components must be equipped in an image display device. A video receiver receives video feeds from both the EO and IR cameras. A video decoder converts each encrypted video stream back to the original format to display the video stream on the screen. An image processing device processes the incoming decrypted video feeds and combines the decrypted video feeds into a single stream to display the image on one screen. A video display device displays the combined stream, where the EO and IR images overlap each other, on the screen. In addition to the components, an image display device may have additional functions, such as adjusting the transparency of each image layer to control the amount of overlap or zooming a specific area of each image for detailed viewing. Overall, the function of integrating IR and EO camera video data on one screen allows a user to simultaneously view both types of images and understand the situation being monitored more completely. The overlap of the two images can provide additional context and detailed information not visible in the two images.

Description

Integrated image providing device for micro-unmanned aerial vehicles}

The present invention relates to an integrated image providing device for a small unmanned aerial vehicle (UAV), and more particularly, to a device that provides a comprehensive and high-quality image of a target area by integrating image feeds. It is suitable for use in a variety of fields including air surveillance, security, inspection, search and rescue operations, and military operations in multiple cameras mounted on a micro UAV.

In recent years, the use of unmanned aerial vehicles (UAVs) has become increasingly prevalent due to their ability to perform a variety of tasks with high efficiency and mobility. In particular, ultra-small UAVs are small and light, and are widely used for air surveillance, security, inspection, search and rescue, and military operations.

However, one of the challenges associated with using micro-UAVs for image acquisition is the limited field of view (FOV) and resolution of each individual camera. This can result in incomplete or low quality images that do not provide a comprehensive view of the target area.

These existing devices have slightly improved image quality and coverage, but they are still needed. For a more advanced integrated image providing device capable of providing a more comprehensive and high-quality image of the target area more accurately and efficiently, the present invention integrates the video feed of the EO/IR camera mounted on the micro UAV and It addresses this need by providing high-quality composite images in real time.

Korean Patent Publication 1020220135446 (2022.10.07) “Method and system for estimating the attitude of the EO/IR device using an unmanned flight device”, “Method for estimating the attitude of an EO/IR device using an unmanned flight device and system is initiated. The posture estimation method of the EO/IR device controls PT (Pan and tilt) of the EO/IR device so that the unmanned aerial vehicle in flight comes to the center of the image displayed on the image display of the EO/IR (Electro-Optical and Infrared Sensors) device doing; moving the unmanned aerial vehicle to receive PT information of EO/IR devices corresponding to different positions of the unmanned aerial vehicle; and estimating the posture of the EO/IR device based on PT information of the EO/IR device corresponding to the different positions of the unmanned aerial vehicle.”

Korean Registered Patent No. 1024718420000 (2022.11.24) “EO/IR image simulation method for LVC-based drone tactical training” shows “Simulating a background image of thermal image processing of a virtual environment terrain image; and (5) performing, by the drone simulator, thermal image simulation of the target object through the IR image. According to the EO/IR image simulation method for LVC-based drone tactical training proposed in the present invention, the operating principle of the sensor gimbal in an environment provided by describing EO/IR sensor images in a virtual environment of LVC-based drone tactical training Perform camera gimbal simulation that simulates, perform screen size simulation by zoom magnification of sensor, perform simulation of EO image and IR image by switching image mode, and perform thermal image of virtual environment terrain image through IR image Actual drone operation by depicting the camera image of the actual EO/IR sensor in a virtual environment that models the actual real environment by performing background image simulation of processing and configuring to perform thermal image simulation of the target object through IR image It is possible to provide an environment such as camera operation in and train. In addition, according to the EO/IR image simulation method for LVC-based drone tactical training of the present invention, a camera image of an actual EO/IR sensor is depicted in a virtual environment modeling a real real environment, so that the camera operation in real drone operation can be achieved. By providing an environment and enabling training, it is possible to create a training environment similar to the actual environment so that the training effect can be increased.”

Korean Patent Publication No. 1020220135446 (2022.10.07) “Method and system for estimating attitude of EO/IR device using unmanned flight device” Korean Registered Patent No. 1024718420000 (2022.11.24) “EO/IR video simulation method for LVC-based drone tactical training”

The present invention is proposed to solve the above problems of the previously proposed methods, while the video receiver receives the video feed from the EO and IR cameras, the video decoder decodes the encrypted video stream back to its original form, The image processing unit processes the incoming decoded video feeds and combines them into a single stream, and the video display unit displays a combined stream in which EO and IR images overlap each other on the screen.

In addition, the present invention provides a user interface unit so that the user can control the overlapping amount by adjusting the transparency of each image layer in the integrated image providing device for a micro-UAV or expand a specific area of each image to view additional features such as It has the other purpose of being able to provide additional context and details not visible in the two images themselves. .

An integrated video providing device for a micro-UAV according to the features of the present invention for achieving the above object is a video receiver for receiving a video feed transmitted by encrypting an image taken from an EO and an IR camera by the device of the micro-UAV; and

A video decoder for decoding and converting the encrypted video feed of the video receiver back to its original format; and

an image processing unit that processes the incoming decoded video feeds and combines them into a single stream; and

It is characterized in that it includes a video display unit for displaying a combined stream in which visible ray image (EO) and infrared image (IR) images overlap each other on a screen using a single stream obtained through the image processing unit.

For military use, it can be applied to micro-UAVs that are easy to carry and operate by one person. The micro-UAVs are equipped with both EO and IR cameras and can be remotely controlled using a wireless remote control, and can be used for reconnaissance, surveillance and other military purposes that are necessary. suitable for use as Automatically detect and highlight motion detected in an image. It includes an image display device that uses motion-detection algorithms to identify areas of the image that are moving, then magnifies or highlights those areas for a closer look by the user. The function of an image display device is that certain areas of an image displayed for a more detailed view add functionality and usability to the device so that the user can more easily and quickly identify important information in the displayed image.

1 is a background view of an integrated image providing device for a micro-UAV using a micro-UAV according to an embodiment of the present invention.
Figure 2 is a configuration diagram of an integrated image providing device for a micro-sized UAV according to an embodiment of the present invention.
3 is a compact optical camera
4 is a compact thermal imaging camera
5 is an embodiment of an integrated image providing device for a micro-sized UAV of the present invention
6 is a photograph of a person detection experiment in an IR camera image

Hereinafter, preferred embodiments will be described in detail so that those skilled in the art can easily practice the present invention with reference to the accompanying drawings.

1 is a diagram showing a background view of an integrated image providing device for a micro-UAV using a micro-UAV according to an embodiment of the present invention. As shown in Figure 1,

It is a background diagram of an integrated image providing device for a micro-UAV using a micro-UAV, which is the background of the present invention.

The micro-UAV 120 is a 500g-class portable micro-miniature surveillance and reconnaissance micro-UAV capable of vertical take-off and landing, and capable of filming and transmitting in a military operation area by simultaneously mounting an EO/IR camera.

It is an ultra-compact UAV equipped with automatic target tracking and route flight support, real-time route and target correction function, emergency mode automatic return function, and portable storage case.

The tiny UAV features automatic target tracking and flight path assistance, is equipped with cameras and sensors, and uses computer algorithms to track targets and establish flight paths. For real-time route correction, the drone is equipped with GPS and other sensors and uses computer algorithms to correct the flight route in real time. It has an emergency mode automatic return function. To this end, drones are equipped with sensors such as GPS for safe emergency landing and automatically handle emergency mode using computer algorithms.

The micro drone has a compact and streamlined design and can support more than 500 grams. The drone has a small camera module on the underside that houses the EO and IR cameras. The battery is inside the body of the drone and can be easily replaced. The RF communication module is mounted on the top and has a range of up to 5 km. The UAE can fly at speeds of up to 50 km/h and reach altitudes of up to 500 m.

The UAE using GCS refers to the UAE that is piloted using the ground control system (130, GCS). GCS is a remote control center that allows drone operators to monitor and control flight paths, cameras and other functions in the UAE from a safe distance. A GCS typically consists of a communication link to a computer or tablet, controller, or drone.

UAE with GCS allows users to fly beyond the sights of the UAE, which is ideal for the application. GCS, such as Search and Rescue, Surveillance, Inspection and Mapping, provides users with real-time data such as altitude, speed, GPS location, and video feeds from UAE cameras. Users can use this data to control the UAE's flight path and adjust camera angles to get a better view of the target area.

UAEs that use GCS typically use advanced technologies such as GPS, sensors, and computers. Algorithms that provide stable flight and reliable operation. Additionally, GCS generally provides various functions such as automatic route planning, obstacle avoidance, and emergency mode to ensure safe and efficient operation of the UAE.

KCMVP is an abbreviation for Korea Certified Multipurpose Security Verification Program. It is an encryption technology standard developed and managed by the National Intelligence Service (NIS) of the Korean government to ensure secure communication between government agencies.

In the KCMVP standard, NIS meets strict security requirements. The cryptographic algorithms used in KCMVP are designed to protect data confidentiality, integrity and availability.

KCMVP is mandatory for all government agencies and organizations handling confidential information. NIS provides certification and testing services to ensure that the cryptographic products and solutions used by these organizations meet the KCMVP standards.

KCMVP has been widely adopted in various industries in Korea, including finance, healthcare, and telecommunications. The KCMVP standard is considered one of the most stringent encryption standards in the world and has received international recognition.

KCMVP stands for Korea Certified Multi-Purpose security Validation Program.

The purpose of UAVs is to provide soldiers with real-time battlefield information so they can make informed decisions and react accordingly. UAVs are equipped with advanced sensors and cameras to monitor and reconnoiter enemy combatants, while providing soldiers with real-time information to make tactical decisions.

The ground control system 130 is a related hardware device (communication modem ground control device) for remote operation of the UAV system, two-way communication technology and a small, lightweight, low power, low power mounted information exchange terminal device technology, ground control for an efficient user interface It is equipped with device construction technology, data compression technology for efficient transmission of massive data, data encoding anti-hacking technology for data security, and geo fencing control technology for drone system flight paths.

The integrated image providing device 110 for a micro-unmanned aerial vehicle of the present invention

A video receiver for receiving a video feed transmitted by encrypting an image taken from an EO and an IR camera by a device of a micro-sized UAV; and

A video decoder for decoding and converting the encrypted video feed of the video receiver back to its original format; and

an image processing unit that processes the incoming decoded video feeds and combines them into a single stream; and

It is characterized by a configuration including a video display unit for displaying a combined stream in which visible ray image (EO) and infrared image (IR) images overlap each other on a screen using a single stream obtained through the image processing unit.

The integrated video providing device 110 for the micro-UAV may receive the data stream of the micro-UAV 120 through the ground control system 130, or directly receive the data stream of the micro-UAV 120 as needed.

2 is a configuration diagram of an integrated image providing device for a micro-unmanned aerial vehicle according to an embodiment of the present invention. As shown in FIG. 2, the integrated image providing device 110 for a micro-unmanned aerial vehicle according to an embodiment of the present invention

A video receiver 220 for receiving a video feed transmitted by encrypting an image taken from an EO and an IR camera by a device of a micro-sized UAV;

A video decoder 230 that decodes and converts the encrypted video feed of the video receiver back to its original format; and

An image processing unit 240 that processes incoming decoded video feeds and combines them into a single stream; and

A video display unit 250 that displays a combined stream in which visible ray image (EO) and infrared image (IR) images overlap each other on a screen using a single stream obtained through the image processing unit;

It may be configured to include a control unit 210 that controls the video receiver, video decoder, image processing unit, and video display unit.

The controller 210 manages the overall operation of the imaging device, and the video receiver 220 receives video signals captured by the EO camera and the IR camera. The image decoder 230 decodes the encrypted video signal and a storage unit (not shown) stores the video signal for further processing.

The GPU calculation unit in the image processing unit 240 performs various image processing functions including geometric correction, lens distortion correction, and noise suppression. The GPU computing unit also enables the imaging unit to perform real-time image processing and display.

The video display unit 250 is an image display device and displays an EO camera image and an IR camera image on a screen. The video display unit 250 may also determine a specific area to display a specific part of the image.

The essence of the present invention relates to an apparatus for simultaneous reception and superimposition of IR and EO camera images for display. More specifically, the present invention relates to an apparatus for combining images captured by an IR camera and an EO camera to provide a single superimposed image for display.

Infrared (IR) and electro-optical (EO) cameras are widely used to capture images in a variety of environments. IR cameras are used to capture images in low-light and no-light environments, whereas EO cameras capture images in daylight and well-lit environments. These cameras have different operating principles and capture images in different spectral ranges.

In applications, it is desirable to combine images captured by IR and EO cameras to provide a more complete and informative image. For example, in military and surveillance applications, combining the two types of imagery can help identify potential threats and improve situational awareness. There is a need for a device that can simultaneously receive and superimpose IR and EO camera images.

The present invention provides an apparatus for simultaneous reception and superimposition of IR and EO camera images for display. The device includes an IR camera and an EO camera, each mounted on a single platform, namely UAE. Images captured by the cameras are processed and superimposed to provide a single composite image for display.

The multifunctional imaging device described above provides various advantages over conventional imaging devices. It is possible to display images from multiple sources, process and display images in real time, and display specific areas. It also provides various image processing functions to improve the quality of displayed images.

The device contains a processor for processing images captured by the camera. A processor combines the images and performs image enhancement to improve the quality of the composite image. The device also includes a display for displaying the composite image.

The device may include a variety of additional features such as zoom and pan functions, image recording and storage, and transmission of images to a remote location.

The image processing unit 240 processes images as a device for receiving images captured from two cameras and combining them into one. composite image. The processing unit may include hardware and software to perform image processing such as image enhancement, image fusion, and image segmentation. The processing unit may also include algorithms to adjust parameters of the individual images to optimize the quality of the composite image.

As the images are processed and combined, the composite image is displayed on a high-resolution monitor. Alternatively, a head-up display (HUD) may be an embodiment of the monitor. That is, the display could be integrated into a helmet or goggles for use in military or other professional applications.

The IR and EO cameras are mounted on a single platform, UAE, and are aligned with overlapping fields of view. When shooting starts, both cameras start capturing images simultaneously. IR cameras capture enemy heat signatures, and EO cameras visually capture the environment.

The captured images are sent to a processing device where they are processed and combined into one composite image. The processing unit performs image enhancement to improve the quality of individual images, such as adjusting contrast and brightness. The processing unit then performs image fusion combining the IR and EO images into a single composite image. This is done using an algorithm that analyzes each image's pixel values and combines them according to their relative strengths and weaknesses. The resulting composite image shows enemy heat signatures and visual images of the environment superimposed on top of each other.

The composite image is then displayed. On a high-resolution monitor or heads-up display (HUD), the display may include additional features such as zoom and pan capabilities to allow the user to focus on a specific area of the composite image. In the example scenario, the composite image shows enemy soldiers' positions overlaid on the visual environment, allowing them to navigate buildings and engage the enemy more accurately and effectively.

3 is a miniature optical camera.

The ultra-compact EO optical camera is a type of camera designed to deliver high quality images while being small, lightweight and portable. EO stands for "electro-optical" and refers to the use of a light-sensitive device such as a CCD or CMOS sensor to convert incoming light into a digital signal that can be processed and displayed.

Ultra-compact EO optical cameras generally have a small form factor, making them easy to carry and transport. In addition, it can operate for a long time on battery power due to low power consumption.

The ultra-compact EO optical camera is small in size but can offer a variety of features, including: With high resolution imaging, zoom capability and low light performance. Some models may also offer advanced image processing features such as image stabilization, color correction and automatic exposure control.

These cameras are commonly used for aerial photography and videography, surveillance and security, industrial inspection, and even consumer photography. It is often used in situations where portability and convenience are important, such as outdoor activities or remote locations.

One of the advantages of compact EO optical cameras is their versatility. Its small form factor and versatility allow it to be used in a variety of situations, from capturing high-quality images and video in extreme environments to providing surveillance and security in public spaces. Overall, the compact EO optical camera is a useful tool for anyone requiring high-quality imaging in a portable and easy-to-use package. Its small size and versatile features make it a versatile and useful device for a variety of applications and can be mounted in the UAE.

4 is a compact thermal imaging camera

A compact thermal infrared (IR) camera is a type of camera designed to detect and display heat signatures in the environment. Unlike conventional cameras that detect and display visible light, thermal IR cameras detect infrared light emitted by an object based on its temperature.

Miniature thermal IR cameras are typically small in size and low power consumption, making them portable and long-lasting. It can also provide functions such as high-resolution imaging, temperature measurement, and real-time video streaming. One of the main advantages of compact thermal imaging IR cameras is their ability to detect heat signatures at low temperatures. It can be used in bright or completely dark conditions, making it useful for a wide range of applications. For example, thermal IR cameras are commonly used for firefighting, search and rescue operations, industrial inspection, surveillance and security, and military purposes.

In firefighting, thermal IR cameras can help firefighters identify the location of hotspots or hidden fires. You can target more effectively and minimize damage in burning buildings. In search and rescue operations, thermal IR cameras can help locate missing persons by detecting body temperature signatures in low-light or total darkness conditions. In industrial inspections, thermal IR cameras can identify thermal signatures that can indicate mechanical problems or overheating of machinery or equipment. In surveillance and security applications, thermal IR cameras can detect human and animal movements in low-light conditions, providing an extra layer of security for buildings or outdoor spaces. Overall, a compact thermal IR camera is a useful tool. It is for anyone who needs to detect and display heat signatures in the environment. Its small size and versatility make it a versatile and useful device for applications ranging from firefighting, search and rescue to industrial inspection, surveillance and security, and military purposes.

5 is an embodiment of an integrated image providing device for a micro-unmanned aerial vehicle according to the present invention.

The integrated video providing device has a function of displaying the flight trajectory of the UAE separately from the EO/IR video taken by the current camera. This allows users to view flight trajectories or EO/IR images on their own without overlaying other information on top.

To achieve this, the system uses software and user interface design to allow the user to switch between different modes or views. For example, users can switch between a mode that displays only flight trajectories and a mode that displays only EO/IR images. Apart from the process of displaying flight trajectories and EO/IR images, the following steps may be included:

A user interface design system includes a user interface that allows the user to switch between different modes or views. This can include buttons, sliders, or other interactive elements that users can use to select different modes.

When the user selects the flight trajectory mode, the system displays the flight trajectory of the UAE overlaid on a map or other visualization in the area. This can include information such as the aircraft's position, altitude, speed and direction.

EO/IR image display: When the user selects EO/IR image mode, the system will display the most recent EO/IR image captured by the camera in the UAE. This can include live video feeds or still images that are updated in real time.

Mode switching: Users can switch between flight trajectory mode and EO/IR image. A mode using the user interface allows the user to view the flight trajectory or EO/IR image on its own without overlaying other information on top.

Ability to display overall flight trajectories and EO/IR images require separate software and user interface design that allows users to switch between different modes or views. This provides flexibility and allows users to view the information most relevant to their needs at any given time.

6 is a photograph of a person detection experiment in an IR camera image.

The technology for detecting people in IR (infrared) images is based on computer vision algorithms and machine learning technology. IR cameras capture images of the environment in the form of thermal radiation emitted by objects according to their temperature. A human body that is warmer than its surroundings emits more thermal radiation and is therefore easier to detect in IR images. The process of detecting a person in an IR image includes image pre-processing, feature extraction and classification. These steps are:

Image pre-processing: IR images captured by the camera are first pre-processed to enhance contrast and remove noise or artifacts. This may include techniques such as histogram equalization or spatial filtering.

Feature extraction: Next, features are extracted from pre-processed IR images related to human detection. Common characteristics include shape, texture, and temperature distribution.

Classification: A machine learning algorithm is then used to classify the features extracted from the IR images as "human" or "non-human." These algorithms learn to recognize patterns of features that indicate the presence of people in images.

There are several types of machine learning algorithms that can be used for:

Support Vector Machines (SVMs): These algorithms are trained to find the optimal boundary between “human” and “non-human” classes in a feature space.

Artificial Neural Networks (ANNs): These algorithms consist of layers of interconnected artificial neurons that learn to recognize patterns in feature space.

Convolutional Neural Networks (CNN): This algorithm is a type of ANN specifically designed for image classification tasks. It uses a series of convolutional and pooling layers to learn features of different scales and orientations.

Once machine learning algorithms are trained on large datasets of labeled IR images, they can be used to detect people in new IR images in real time. The algorithm analyzes the features extracted from the new image and predicts whether a person is present or not.

Overall, the technology for detecting people in IR images uses computer vision algorithms and machine learning techniques to extract relevant features and classify them as "human" or "non-human". This technology has applications in a variety of fields, including security, search and rescue, and medical imaging.

When such an IR image and an EO image overlap, when a person is recognized in the IR image, a display emphasizing this can be displayed so that the user can easily determine it.

Infrared (IR) and visible light images are fused to create a high-resolution, comprehensive image rich in information. Below are some techniques and formulas used to fuse these images.

Pixel-level fusion: In this technique, images are fused at the pixel level. The corresponding pixels of the visible light image and the IR image are fused together. The simplest way to do this is to take the average of two pixel values, known as average fusion.

Wavelet transform-based fusion: Wavelet transforms are used for: Decompose the image into different frequency bands. High frequency bands contain fine details and low frequency bands contain coarse details. The wavelet coefficients of the two images are combined to create a fused image.

Convergence based on Intensity-Hue-Saturation (IHS) transformation: In this technique, IHS transformation is applied. Separate visible light images into intensity, hue, and chroma components. After replacing the intensity component with an IR image, the IHS transformation is applied again to create a fusion image.

image and infrared image. The IHS method converts a visible light image and an infrared image from an RGB color space to an IHS color space. In the IHS color space, the intensity channel represents brightness information of an image, and the hue and saturation channels represent color information of an image.

The formula for converting an RGB image to the IHS color space is:

I = (R + G + B) / 3

H = arccos [0.5 * ((R - G) + (R - B)) / sqrt((R - G)^2 + (R - B) * (G - B))]

S = 1 - 3 * min(R, G, B) / (R + G + B)

where I is the intensity channel, H is the hue channel, and S is the saturation channel.

In order to fuse the visible light image and the infrared image in the IHS method, the intensity channel of the infrared image is replaced with the intensity channel of the visible light image in the IHS color space. The formula for fusing the two images is:

I_fused = α * I_visible + (1 - α) * I_infrared

H_fused = H_visible

S_fused = S_visible

where I_fused, H_fused and S_fused are the intensity, hue and saturation channels of the fused image, respectively. α is a weight that determines the contribution of the visible ray image and the infrared image to the fused image. As the value of α increases, weight is assigned to the visible ray image, and as the value of α decreases, weight is assigned to the infrared image.

The range of α in the above equation is generally between 0 and 1. Here, α=0 means that only the original infrared image is included in the final fusion image, and α=1 means that only the original visible ray image is included in the final fusion image. The value of α determines how much each input image contributes to the final fusion image.

Therefore, in the present invention, the value of α is adjusted to 0.1 to 0.4 to give a weight to the infrared image so that the user can immediately recognize a person.

Principal Component Analysis (PCA) based fusion: PCA is used to extract principal components from two images and then combine the components to create a fused image. The advantage of this technique is that it maximizes the informational content of the fused images.

Laplacian pyramid-based fusion: The Laplacian pyramid is used to decompose an image into multiple levels, each level representing a different level of detail. The pyramid coefficients of the two images are combined to create a fused image.

The specific formulas used for image fusion depend on the technology used, but usually involve a combination of mathematical operations.

Although the present invention has been described with reference to specific embodiments, it is obvious to those skilled in the art that various changes are possible. Equivalents may be substituted for elements without departing from the true spirit and scope of the invention. In addition, many modifications may be made without departing from the essential teachings of the present invention.

110: Integrated video providing device for micro-unmanned aerial vehicle 210: Control unit
220: video receiver 230: video decoder
240: image processing unit 250: video display unit

Claims (1)

In the integrated image providing device 110 for a micro-unmanned aerial vehicle,
A video receiver 220 for receiving a video feed transmitted by encrypting an image taken from an EO and an IR camera by a device of a micro-sized UAV;
A video decoder 230 that decodes and converts the encrypted video feed of the video receiver back to its original format; and
An image processing unit 240 that processes incoming decoded video feeds and combines them into a single stream; and
A video display unit 250 that displays a combined stream in which visible ray image (EO) and infrared image (IR) images overlap each other on a screen using a single stream obtained through the image processing unit;
An integrated video providing device for a micro-unmanned aerial vehicle, characterized in that it comprises a control unit 210 for controlling the video receiver, video decoder, image processing unit, and video display unit.

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