Method for reducing nuclear radiation-induced speckle in video images.

Abstract

A video processor for removing interference due to nuclear radiation is disclosed. The video processor includes a control circuit configured to receive video data from a camera located in a nuclear radioactive environment, identify a first image from the video data, calculate a first brightness value for a first pixel located at a first pixel location in the first image, identify a second image from the video data, calculate a second brightness value for a second pixel located at a second pixel location in the second image, compare the first brightness value with the second brightness value, and update the second image by replacing the second pixel in the second image with the first pixel if the second brightness value is greater than the first brightness value, where the first image corresponds to an earlier time than the second image and the first pixel location and the second pixel location are the same.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of and priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 17 / 815,470, filed July 27, 2022, and entitled "METHOD TO REDUCE NUCLEAR RADIATION INDUCED SPECKLING IN VIDEO IMAGES," the contents of which are incorporated herein by reference in their entirety.

[0002] The present disclosure relates to cameras and imaging interference with nuclear radiation. Summary of the Invention

[0003] In a general aspect, the present disclosure provides a video processor for removing interference due to nuclear radiation. The video processor includes a control circuit having a memory. The control circuit is configured to receive video data from a camera located in a nuclear radiation environment, identify a first image from the video data, calculate a first brightness value for a first pixel located at a first pixel location in the first image, and identify a second image from the video data, the first image corresponding to a time earlier than the second image. The control circuit is further configured to calculate a second brightness value for a second pixel located at a second pixel location in the second image, the first pixel location and the second pixel location being the same. The control circuit is further configured to compare the first brightness value with the second brightness value and, if the second brightness value is greater than the first brightness value, update the second image by replacing the second pixel in the second image with the first pixel.

[0004] In another aspect, the present disclosure provides a video processor for removing interference due to nuclear radiation. The video processor includes a control circuit having a memory. The control circuit is configured to receive a first image from a camera located in a nuclear radioactive environment, receive a second image from the camera, the first image corresponding to a time earlier than the second image, calculate first brightness value data for the first image including brightness values for each pixel in the first image, and calculate second brightness value data for the second image including brightness values for each pixel in the second image. The control circuit is further configured to compare the first brightness data with the second brightness data, where the brightness value of each pixel at a pixel location in the first image is compared with the brightness value of a corresponding pixel at the same location in the second image. The control circuit is further configured to update the second image by replacing pixels in the second image with corresponding pixels in the first image based on the comparison of the first brightness data with the second brightness data.

[0005] In another aspect, the present disclosure provides a video processor for removing interference due to nuclear radiation, the video processor comprising a control circuit with a memory, the control circuit configured to receive video data from a camera located in a nuclear radiation environment, receive data indicative of camera movement, segment the video data into a plurality of consecutive images, and filter the interference due to nuclear radiation from each of the plurality of consecutive images to form a plurality of updated consecutive images. The filtering includes calculating first brightness value data for a first image, the first brightness value data including a brightness value for each pixel in the first image. The filtering further includes calculating second brightness value data for a second image, the second image following the first image, the second brightness value data including a brightness value for each pixel in the second image. The filtering further includes comparing the first brightness data with the second brightness data, wherein the brightness value of each pixel in the first image is compared to the brightness value of a pixel at a corresponding pixel location in the second image. The filtering further includes updating the second image by replacing pixels in the second image with corresponding pixels in the first image based on a comparison between the first luminance data and the second luminance data, and calculating updated second luminance value data for the updated second image, the updated second luminance value data including a luminance value for each pixel in the updated second image. The filtering further includes calculating third luminance value data for a third image, the third image following the second image, the third luminance value data including a luminance value for each pixel in the third image. The filtering further includes comparing the updated second luminance data and the third luminance data, where the luminance value of each pixel in the updated second image is compared with the luminance value of a pixel at a corresponding pixel location in the third image, updating the third image by replacing pixels in the third image with corresponding pixels in the updated second image based on a comparison between the updated second luminance data and the third luminance data, and combining the multiple updated images into updated video data.

[0006] The novel features of the various aspects are set forth with particularity in the appended claims. However, the described aspects, both as to organization and method of operation, may best be understood by reference to the following description taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram of a video processing system according to at least one aspect of the present disclosure.

[0008] [Figure 2] FIG. 1 is a diagram of an exemplary nuclear radiation environment, in accordance with at least one embodiment of the present disclosure.

[0009] [Figure 3] FIG. 1 is a diagram of several components of an exemplary digital camera in accordance with at least one aspect of the present disclosure.

[0010] [Figure 4] 1 is an image including speckles, according to at least one embodiment of the present disclosure.

[0011] [Figure 5] 5 is a filtering result of filtering the image of FIG. 4 in accordance with at least one embodiment of the present disclosure.

[0012] [Figure 6] FIG. 10 is a diagram of a two-frame minimal filtering process for removing interference due to nuclear radiation, in accordance with at least one embodiment of the present disclosure.

[0013] [Figure 7] 7 illustrates the two-frame filtering process of FIG. 6 applied to a video stream, in accordance with at least one embodiment of the present disclosure.

[0014] [Figure 8]FIG. 10 illustrates a two-frame minimal filtering process applied to more than two images at a time, in accordance with at least one embodiment of the present disclosure.

[0015] [Figure 9] 1 is an image including speckles, according to at least one embodiment of the present disclosure.

[0016] [Figure 10] FIG. 1 is a diagram of an image filtering process for removing interference due to nuclear radiation, according to at least one embodiment of the present disclosure.

[0017] The accompanying drawings are not intended to be drawn to scale. Corresponding reference characters indicate corresponding parts in the various views. For clarity, not every part is labeled with a reference character in every drawing. The illustrations described herein illustrate particular embodiments of the invention in one aspect, and such illustrations are not to be construed as limiting the scope of the invention in any way. DETAILED DESCRIPTION OF THE INVENTION

[0018] Video quality of images for inspection and surveillance in areas where cameras are exposed to nuclear ionizing radiation is degraded by temporary bright spots, or speckles, within each video frame. These speckles are the result of the effects of nuclear ionizing radiation (mainly gamma rays) on photosensitive elements. Although individual speckles are temporary, their presence degrades the image and makes it difficult to obtain a clear image. The speckle effect is temporary, with affected pixels randomly distributed within each frame. In addition to being temporary, affected pixels are always biased toward producing a brighter output than is appropriate for the incident light.

[0019] The preferred approach to solving this problem is a digital video filter that outputs the minimum luminance value of each pixel for two or more consecutive frames, thereby filtering out overly bright values induced by radiation. A two-frame minimum filter can significantly improve image quality. Using a filter with more than the minimum of two frames improves image quality but reduces video responsiveness. The number of frames used in the filter can be dynamically adjusted to optimize observation depending on the camera characteristics and on-site activity.

[0020] In one example, a video processor for removing interference due to nuclear radiation may include a control circuit with a memory. The control circuit may be configured to receive video data from a camera located in a nuclear radiation environment, identify a first image from the video data, calculate a first brightness value for a first pixel located at a first pixel location in the first image, and identify a second image from the video data, the first image corresponding to a time earlier than the second image. The control circuit may be further configured to calculate a second brightness value for a second pixel located at a second pixel location in the second image, the first pixel location and the second pixel location being the same. The control circuit may be further configured to compare the first brightness value with the second brightness value and, if the second brightness value is greater than the first brightness value, update the second image by replacing the second pixel in the second image with the first pixel.

[0021] Video filters that time-average successive readings can also introduce speckle into the image. The proposed two-frame minimum filter is based on minimum intensity rather than average value. This process largely overcomes radiation-induced pixel errors. The advantages of this approach are that it requires minimal data, is robust, and is fast. The filter can be quickly applied to the incoming video while continuing to send the filtered video to a user interface where the operator can view it in real time.

[0022] In the field of nuclear radiation, cameras may be used in numerous applications. For example, in inspection applications, such as inspecting fuel rods, reactor interiors, and reactor equipment, cameras may transmit images degraded by radiation-induced speckle. In other examples, cameras may be placed near contaminated areas of a nuclear reactor, such as in or near piping, in or near a vessel, or in or near the reactor core, to perform visual inspections, or near materials activated by previous neutron irradiation, such as spent fuel or waste fuel. An example of an inspection application is a remote robotic assistance system for inspecting and repairing a nuclear reactor. When operating a remote system, random speckle in the video feed can be very distracting to the operator. In some cases, the speckle can make it difficult for the operator to complete their tasks.

[0023] FIG. 1 is a diagram 100 of a camera 140 being subjected to nuclear radiation. As the camera 140 is subjected to the nuclear radiation, it is affected. The camera 140 is recording images and / or video of an object 150 that is under or near the nuclear radiation. The camera 140 may be attached to a motor 142 that allows a user to move the camera 140 to view different aspects of the object 150. For example, the motor 142 may rotate the camera 140. The motor 142 may be communicatively coupled to a video processor 130. The video processor 130 may be located remotely from the camera 140 or may be part of the camera 140 itself. The video processor 130 may relay user input from the user interface 110 to control the motor 142. The motor 142 may send data indicative of the camera's movement to the video processor 130. The camera 140 may be communicatively coupled to the video processor 130. In one example, video processor 130 may be built into the housing of camera 140. In another example, video processor 130 may be external to the housing of the camera, with camera 140 connected wirelessly or by wire to processor 130. In either case, camera 140 is communicatively coupled to video processor 130 and transmits image data and / or video data to video processor 130.

[0024] The video processor 130 includes a video filter 132. The video filter 132 may be configured to edit received images and / or video to remove speckle due to a nuclear radiation field in which the camera 140 is positioned. The processor 130 is communicatively coupled to the memory 120. The memory may be used to store instructions for removing speckle due to nuclear radiation. For example, the memory 120 may store instructions for a two-frame minimum filter. The memory 120 may be accessed by the video filter 132 to perform the two-frame minimum filter. Additionally, the memory 120 may store raw data including speckle and filtered data from which the speckle has been removed.

[0025] The processor 130 is communicatively coupled to the user interface 110. The processor 130 may transmit raw data and / or filtered data to the user interface 110. The user interface 110 may include a display that allows a user to view the raw data and / or filtered video data. Alternatively, the display may be separate from the user interface 110. The user interface 110 may allow a user to update parameters for removing speckle due to nuclear radiation. For example, a user may input parameter adjustments for a two-frame minimum filter, such as adjusting the number of frames from two to a value greater than two. This exemplary adjustment may slow down video responsiveness, but may be necessary if speckle persists for more than two frames. As an example, the video processor 130 may analyze a pixel and inform the user of the number of frames or duration that the pixel contained speckle.

[0026] Speckle can be caused by gamma-ray induced ionization, which causes some pixels in an image frame to randomly brighten. In some instances, the randomly bright pixels may settle in just one frame and no longer appear abnormally bright. In other instances, it may take multiple frames for the pixels to settle and no longer appear abnormally bright. In such cases, the user may input the time or number of frames for the 2 min filter to run to achieve the desired speckle reduction results in the incoming video feed and / or images.

[0027] FIG. 2 illustrates an example of a nuclear radiation environment in which cameras may transmit images and / or video corrupted by radiation-induced speckle. An exemplary reactor design is shown in FIG. 2 and will now be briefly described. The core 244 is composed of multiple parallel, vertically co-extending fuel assemblies 280, although for purposes of this description, other vessel internals may be divided into a lower interior 252 and an upper interior 254. In conventional designs, the function of the lower interior is to support, align, and guide core components and instrumentation, as well as to guide flow within the vessel. The upper interior 254 provides restraint or secondary restraint for the fuel assemblies 280 (only two are shown in the figure for simplicity) and supports and guides instrumentation and components such as control rods 256. The coolant enters the reactor vessel 240 through one or more inlet nozzles 258, flows downward through the annulus between the reactor vessel 240 and the core barrel 260, turns 180° in the lower reactor vessel plenum 261, passes upward through the lower support plate and lower core plate 264 on which the fuel assemblies 280 rest, and flows through and around the assemblies. After exiting the core 244, the coolant flows along the underside of the upper core plate 266 and upward through a plurality of holes 268 in the upper core plate 266. The coolant then flows upward and radially to one or more outlet nozzles 270. Cameras may be installed to allow an operator to inspect any internal or external component of the reactor shown in FIG. 2 . For example, once the reactor is defueled for inspection, an underwater, open area is provided for installing an inspection camera. Even without fuel, the inside of the reactor is in a highly radioactive state (active state) due to neutron irradiation during operation, and some of the structural materials are converted into radioactive isotopes (such as Co60).

[0028] 3 shows a block diagram 300 of an exemplary digital camera 310 that may be used as camera 140 of FIG. 1, where processor 320 may be processor 130 of FIG. 1. Digital camera 310 generates digital images that are stored as digital image files using image memory 330. As used herein, the terms "digital image" or "digital image file" refer to any digital image file, such as a digital still image or a digital video file. In some examples, digital camera 310 captures both motion video images and still images.

[0029] In various examples, the digital camera 310 includes an image capture system 302. The image capture system 302 includes an image sensor 314 and an optical system with a lens 304 for focusing an image of a scene (not shown) onto the image sensor 314 (e.g., a single-chip color CCD or CMOS image sensor). The image capture system 302 has an optical axis 306 directed outward from the front of the lens 304. In some examples, the lens 304 is a fixed-focus lens with a fixed focal length. In other examples, the lens 304 is a zoom lens with focus control, controlled by a zoom-focus motor or actuator (not shown). In some examples, the lens 304 has a fixed lens aperture, and in other examples, the lens aperture is controlled by a motor or actuator (not shown). The output of the image sensor 314 is converted to digital format by an analog-to-digital (A / D) converter 316, and the digital data is provided to a buffer memory 318.

[0030] The buffer memory 318 stores image data from the image capture system 302. The image data stored in the buffer memory 318 may then be processed by the processor 320 using embedded software programs (e.g., firmware) stored in the firmware memory 328. In some examples, a two-frame minimum filter may be stored in the firmware memory 328. In various examples, the processor 320 may be configured to perform digital filtering according to FIGS. 6-8 and 10. In various examples, the user interface 348 may be used to update the software programs stored in the firmware memory 328 using the wireless / wired interface 338. The firmware memory 328 may also be used to store image sensor calibration data and user setting selections. In some examples, the processor 320 includes a program memory (not shown), and the software programs stored in the firmware memory 328 are copied to the program memory before being executed by the processor 320.

[0031] It will be understood that the functionality of processor 320 may be provided using a single programmable processor or multiple programmable processors, including one or more digital signal processor (DSP) devices. Alternatively, processor 320 may be provided by custom circuitry (e.g., one or more custom integrated circuits (ICs) specifically designed for use in digital cameras), or a combination of programmable and custom circuitry. It will be understood that the connectors between some or all of the various components shown in FIG. 3 and processor 320 may be formed by a common data bus. For example, in some instances, the connections between processor 320, buffer memory 318, image memory 330, and firmware memory 328 may be formed by a common data bus.

[0032] The processed images are stored using image memory 330. In some examples, raw images may also be stored in image memory. It is understood that image memory 330 may be any type of memory known to those skilled in the art.

[0033] It will be appreciated that the image sensor 314, timing generator 312, and AID converter 316 may be separately fabricated integrated circuits or may be fabricated as a single integrated circuit, as is common with CMOS image sensors, and in some examples, such a single integrated circuit may perform some of the other functions shown in FIG. 3, including some of the functions provided by processor 320.

[0034] The image sensor 314 is effective to provide motion sequence data or still image data when activated by the timing generator 312. The exposure period of the image sensor 314 is controlled by the timing generator 312, and the exposure level is controlled by controlling the gain (i.e., ISO sensitivity) setting of the AID converter 316. In some examples, the processor 320 also controls one or more lighting systems (not shown), such as LEDs, that may be used to selectively illuminate a scene in the direction of the optical axis 306 to provide sufficient illumination under low light conditions.

[0035] Display interface 344 provides output signals from digital camera 310 to a display 346, such as a flat-panel HDTV display. Digital video or still digital images may be sent to display 346 via display interface 344. In various examples, display 346 is separate from user interface 348. In some examples, display 346 and user interface 348 may be integrated into a single device. User interface 348 allows an operator to move digital camera 310 via motors 360. User interface 348 sends commands from the operator to processor 320 via wireless / wired interface 338. Processor 320 uses these commands to control motors 360 to move the camera as desired by the operator. For example, in some examples, motors 360 may rotate camera 310 in two degrees of freedom (pan and tilt). In some examples, motors 360 may move the camera in six degrees of freedom (three rotations and three translations). The motor 360 transmits motion data of the motor 360 to the processor 320. The processor 320 can track the movement of the camera 310 from the motion data.

[0036] FIG. 4 shows an image 400 from inside a test cell where nuclear radiation is present. Image 400 shows a lead block 410 resting on a support rail 420. Image 400 exhibits speckle 430 throughout the image due to nuclear radiation. To remove the speckle 430, image 400 can be used in a two-frame min filter together with a second image of the same scene. The two-frame min filter begins by acquiring at least two images. In some instances, the two images are consecutive frames from a video. In other instances, the two images may be non-consecutive frames from a video. In yet another instance, the two images may be two still images unrelated to the video. A processor determines the brightness value of each pixel in the at least two images. In some instances, more images may be used, but using more images reduces the responsiveness of the real-time video. Pixels at the same pixel locations between the two images are compared. If the brightness value of the second pixel is brighter than the first pixel, the pixel in the second image is replaced with the pixel in the first image. If the brightness value of the second pixel is not brighter than the first pixel, the second pixel is not replaced. If more than two images are used, the brightness of the pixel at the current pixel location between the images is compared. The pixel with the lowest brightness is placed at the pixel location of the last image in the list. By performing the same comparison and replacement at different pixel locations, speckle 430 can be removed from image 400.

[0037] In some examples, the camera may be moved by a motor between two or more images. This camera movement is taken into account in the two-frame minimum filter. Camera movement changes the pixel locations of pixels that must be compared between images. In other words, pixel locations in the first image are mapped to pixel locations in the second image, and pixel values from the first frame are added (resampled) to the equivalent pixel locations defined by the second image. This allows for comparison of pixel intensities at the same locations in the two images. If there are more than two images, pixel locations from the earlier images in the list may be mapped to pixel locations in the last (newest) image in the list. This allows for brightness comparison between images based on motor movement between images. This process allows for comparison of pixels that show the same part of the object being viewed, even when the camera is moving. This allows the two-filter minimum process to be applied to the live image stream and takes camera movement into account.

[0038] FIG. 5 shows an image 500 corresponding to the updated / filtered image 400 after the speckle 430 has been removed using a two-frame minimal filter. As can be seen from FIG. 5, a simple two-frame minimal filter significantly improves image quality, substantially eliminating the speckle 430. In some instances, additional frames may be required to remove the speckle 430. Using additional frames can improve image quality, but at the expense of video responsiveness. The number of frames used may be dynamically adjusted to optimize observation based on camera characteristics and scene activity. In some instances, an operator may input the number of frames to use via a user interface.

[0039] A video processor, such as processor 130 or processor 320, may be configured to implement a digital filter, such as a two-frame minimal filter. Various aspects of the digital filter may be implemented according to FIG. 6. FIG. 6 is a diagram 600 illustrating a two-frame minimal filtering process 650 applied to two images. In step 602, video data and motion data from a camera in a nuclear radiation environment are received by the video processor. If the video data is analog video data, the video processor proceeds to step 604, where the analog video data is converted to digital video data, and then proceeds to step 606. If the video data is already digital video data, the process proceeds directly to step 606. In step 606, two images are selected from the video data by the video processor. In various examples, the two images are consecutive in time. In some examples, the two images are separated by a predetermined time. For example, the video processor may be configured to calculate a period of time it takes for the nuclear radiation interference of a pixel in the image to settle to a true value. In other words, the video processor may determine the time it takes for a pixel that has brightened due to nuclear radiation interference to return to its normal state, and in one example, the time between the two images may be equal to or greater than the determined time it takes for the pixel to return to its normal state.

[0040] In various examples, a user may use an interface to select whether images should be consecutive in time or have a time gap between two images based on image quality and desired video responsiveness. In some examples, the video processor may select the time between images and / or the number of images to employ to achieve the user-provided video responsiveness and image quality. For example, if a user inputs that increased video responsiveness is desired, the video processor may automatically shorten any gap time between images. By shortening the gap time, image quality may or may not be affected. To improve image quality, a user may select for the video processor to use more than two image frames in a two-frame minimum filter (see 850 in FIG. 8). These additional frames may be consecutive in time, or there may be a time gap between these additional frames.

[0041] Returning to FIG. 6 , once the two frames are selected, the video processor then performs a two-frame minimal filtering process 650. The two-frame minimal filtering process 650 continues from step 608 to step 628 and ends when the output image is filtered. In step 608, the video processor calculates the luminance value of each pixel in the two images. The pixel location and the pixel luminance value may be recorded together. In step 610, the video processor begins examining all pixel locations by selecting pixel locations in the second image one by one to compare with the first image. In step 612, the video processor checks motion data received by the camera to determine whether the camera moved between the two images. In various examples, the video data may be time-stamped, and the motion data may be time-stamped, allowing the video processor to calculate whether the camera moved between the images. Alternatively, camera motion may be estimated and image alignment determined by directly comparing consecutive frames using various techniques, such as pixel-based alignment, feature-based alignment, or Fourier-based alignment. If the camera did not move between images, the video processor proceeds along the "no" branch to step 618. In step 618, the pixel location in the first image is recorded as the same as the second pixel image location, and the video processor proceeds to step 620.

[0042] If the camera moved between the images, the video processor proceeds along the "yes" branch to step 614. In step 614, the video processor maps pixel locations in the first image to pixel locations in the second image based on the camera motion. The video processor then adds (resampling) pixel values from the first frame at equivalent pixel locations defined by the second image so that they can be compared. In some examples, new pixel luminance values may be calculated for the added pixel values from the first frame, and these new luminance values are used to compare with the pixel luminance values of the second image. In some examples, camera motion may cause the object in the second pixel to move out of the first image, in which case the video processor cannot compare the brightness of the first and second images. In step 616, the video processor determines whether camera motion has caused the pixel location in the second image to move out of the first image. If the pixel location in the second image has moved out of the first image, a pixel luminance comparison between the images is not possible, and the video processor proceeds along the "yes" branch to step 628. If the pixel location of the second image is within the first image, the video processor proceeds along the "no" branch to step 620. Once the pixel location within the first image is known, the video processor proceeds to the comparison step 620.

[0043] In step 620, the video processor compares the luminance value of the pixel at the pixel location in the second image with the luminance value of the pixel at the pixel location in the first image. In step 622, the video processor determines whether the pixel in the second image is brighter than the pixel in the first image. If the second pixel is brighter than the first pixel, the video processor proceeds along the "yes" branch to step 624. In step 624, the second image is updated by replacing the pixel at the pixel location in the second image with the pixel at the pixel location in the first image. The video processor then proceeds to step 628. If the first pixel is brighter than the second pixel or is the same brightness as the second pixel, the video processor proceeds along the "no" branch to step 628. If the pixel in the first image is brighter than the pixel in the second image, nothing is done to the pixel in the second image. In step 628, the video processor checks whether the luminance values of each pixel location in the second image have been compared. If there are more pixel locations in the second image to compare, the video processor proceeds along the "no" branch to step 610, where the video processor selects another pixel location and performs steps 612 through 628. The video processor repeats steps 610 through 628 until all pixel locations in the second image have been selected and compared with the first image. Once all pixel locations in the second image have been compared, the two-frame minimal filtering process 650 is complete, and the video processor proceeds along the "yes" branch to step 630. In step 630, an updated second image is sent to the user interface for viewing by the operator. In the updated second image, speckle due to nuclear radiation is significantly reduced, and in some cases, completely eliminated. In various examples, the filtering process may be performed in real time, allowing the operator to view the updated image from the camera in real time.

[0044] In some examples, the two-frame minimal filter process 650 may update the first image together with the second image, which is performed in a similar manner to that described above, except that the second raw image data is used to update the first raw image data.

[0045] A video processor, such as processor 130 or processor 320, may be configured to implement a digital filter, such as a two-frame minimal filter. Various aspects of the digital filter may be implemented according to FIG. 7. FIG. 7 shows a diagram 700 illustrating a two-frame minimal filtering process 650 applied to every frame of a video stream. In step 702, video data and motion data from a camera in a nuclear radiation environment are received by the video processor. If the video data is analog video data, the video processor proceeds to step 704, where the analog video data is converted to digital video data, after which the video processor proceeds to step 706. If the video data is already digital video data, the video processor proceeds directly to step 706. In step 706, the video data is decomposed into a number of digital image frames that make up a section of a live video stream or video file. These digital image frames are contiguous in time. For example, a first frame begins a video stream, a second frame sequentially follows the first frame, a third frame sequentially follows the second frame, and so on until the video stream ends with a last frame.

[0046] In step 708, the first two images or frames are selected. The two images are then subjected to the two-frame minimal filter process 650 described above with reference to FIG. 6. The output of the two-frame minimal filter process 650 is the more recent frame after being updated by the filtering process. In some examples, more than two images may be selected in step 708, and the selected number of frames are subjected to the two-frame minimal filter process 850 (FIG. 8). In such cases, the most recent frame of the number of frames input to the two-frame minimal filter process 850 is updated and output from the two-frame minimal filter process 850. In either case, once the most recent frame has been updated by one of the two-frame minimal filter processes 650, 850, the video processor may proceed to step 710. In step 710, the video processor checks whether all images or frames in the video data have been filtered. If all frames have not been filtered, the video processor proceeds along the "no" branch to step 712.

[0047] In step 712, the video processor filters the next frame in the video data. For example, if filtering is performed using only two images, the first image is the immediately previous raw (unupdated) second image, and the second image is the next frame in time that has not yet entered the filtering process. These two images are sent to the two-frame minimal filtering process 650. For example, the first two images in the video data may be subjected to the two-frame minimal filtering process 650. The next two images subjected to the two-frame minimal filtering process 650 may be the unfiltered second image and the third image that temporally follows the second image. The next images subjected to the two-frame minimal filtering process 650 may be the unfiltered third image and the fourth image that temporally follows the third image. This process continues until all frames in the video data have been filtered. In other words, the video processor repeats the cycle from step 712 back to 650 until all images in the video data have been subjected to the filtering process. Once all images have been subjected to the filtering process, the video processor proceeds along the "yes" branch to step 714. In step 714, the video processor sends the filtered video data to the user interface for viewing by the operator.

[0048] In certain examples, more than two frames may be sent to a two-frame minimal filter process, such as two-frame minimal filter process 850. In step 712, if there are more than two frames to be filtered, the next frames input to the two-frame minimal filter process 850 are shifted in time by one frame. For example, if frames 1 through 6 are sent simultaneously to the two-frame minimal filter process 850, then in step 712 the next frames input to the two-frame minimal filter process 850 will be frames 2 through 7. All frames sent to the two-frame minimal filter process 850 are raw, or unfiltered frames. This process continues until all video frames have been video filtered. Once all images have been filtered, the video processor proceeds along the "yes" branch to step 714. In step 714, the video processor sends the filtered video data to a user interface for viewing by an operator.

[0049] In various examples, video data may be received by a video processor in real time. An advantage of the two-frame minimal filtering 650 and 850 is that the video data can be filtered in real time and sent to an operator for viewing. For example, the video processor may receive the video data as packets of video data in time. The video processor may filter the packets of video data to remove speckle and send updated video data before the video processor receives the new packets of video data. This allows the updated video data to be delivered to the operator in real time.

[0050] A video processor, such as processor 130 or processor 320, may be configured to implement a digital filter, such as a two-frame minimum filter 850. Various aspects of the digital filter may be implemented according to FIG. 8. FIG. 8 shows a diagram 800 illustrating a two-frame minimum filtering process 850 applied to multiple frames simultaneously. The two-frame minimum filtering process 850 is very similar to the two-frame minimum filtering process 650. The main difference between the two is that the two-frame minimum filtering process 850 can be applied to more than two images simultaneously, while the two-frame minimum filtering process 650 can be applied to only two images simultaneously. For the sake of brevity, not all of the similarities between the two-frame minimum filtering processes 650 and 850 will be described in detail.

[0051] In step 802, video data and motion data from a camera in a nuclear radiation environment are received by a video processor. If the video data is analog video data, the video processor proceeds to step 804, where the analog video data is converted to digital video data, and then proceeds to step 806. If the video data is already digital video data, the video processor proceeds directly to step 806. In step 806, the video processor selects a group of images from the video data. The group of images may include more than two images. In various examples, the images included in the group may be consecutive in time. In some other examples, the images included in the group need not be consecutive in time, and there may be any time interval between each image included in the group. Once the group of images is selected, the video processor then performs a two-frame minimal filtering process 850. The two-frame minimal filtering process 850 continues from step 808 to step 828, and ends when all images included in the group have been filtered.

[0052] In step 808, the video processor calculates the luminance value of each pixel in each image. The image location of the pixel and the luminance value of the pixel may be recorded together. In step 810, the video processor begins examining all pixel locations by selecting pixel locations in the most recent image one by one to compare between images in the group. In step 812, the video processor checks motion data received by the camera to determine whether the camera moved between any images in the group. In various examples, the video data may be time-stamped, and the motion data may be time-stamped, allowing the video processor to determine whether the camera moved between images. If the camera did not move between images, the video processor proceeds along the "no" branch to step 818. In step 818, the pixel location is recorded as the same in all images, and the video processor proceeds to step 820.

[0053] If the camera moved between the images, the video processor proceeds along the "yes" branch to step 814. In step 814, the video processor maps pixel locations in each image to pixel locations in the most recent image in the collection based on the camera motion. The video processor then adds (resampling) pixel values in each image at equivalent pixel locations defined in the most recent image to enable comparison. In some examples, a new pixel brightness value may be calculated for each added pixel value, and this new brightness value is used to compare with the pixel brightness value of the most recent image. In other words, the video processor takes into account the shift in pixel locations in each image due to camera motion so that pixel brightness values can be compared between images. In some examples, camera motion may cause an object in one of the pixels to move out of its corresponding image, in which case the video processor cannot compare the brightness of that pixel location in that image with the brightness of the pixel location in the other images in the collection. In step 816, the video processor checks that camera motion has not caused all adjusted pixel locations to move out of their corresponding images. If the adjusted pixel locations are all outside the corresponding images, then a pixel intensity comparison between the images cannot be made and the video processor proceeds along the "yes" branch to step 826. If the adjusted pixel location is in at least some of the images included in the group, then the video processor proceeds along the "no" branch to step 820. Once the pixel intensity values at the pixel locations and camera motion have been taken into account for the images, the video processor proceeds to the comparison step 820.

[0054] In step 820, the video processor compares pixel luminance values corresponding to the pixel luminance at the identified pixel location in each image. In some examples, if the camera moved between images, the pixel luminance at a location is calculated based on the camera motion, as described above. In step 822, the video processor determines whether the most recent image has the minimum pixel luminance value. If the most recent image has the minimum pixel luminance value, the video processor proceeds along the "yes" branch to step 826. If another image with the minimum pixel luminance value is included in the group, the video processor proceeds along the "no" branch to step 824. In step 824, the pixel in the most recent image is replaced with the pixel with the minimum luminance value. In some examples, the pixel with the minimum luminance value results from additions or resampling due to camera motion. In step 826, the video processor checks whether the luminance values at each pixel location in the most recent image have been compared. If there are more pixel locations in the current image to compare, the video processor proceeds along the "no" branch to step 810, where the video processor selects another pixel location and performs steps 812-826. The video processor repeats steps 810-826 until all pixel locations in the current image have been selected and compared. Once all pixel locations have been compared, the two-frame minimal filtering process 850 is complete, and the video processor proceeds along the "yes" branch to step 828. In step 828, an updated image, the current filtered image, is sent to the user interface for viewing by the operator. In the updated image, speckle due to nuclear radiation has been significantly reduced, and in some cases completely eliminated. In various examples, the filtering process may be performed in real time, allowing the operator to view updated images from the camera in real time.

[0055] 9 and 10 illustrate another image filtering process for removing speckle due to nuclear radiation. FIG. 9 shows an image from inside a test cell where nuclear radiation is present. Image 900 shows a lead block 910 resting on a support rail 920. Image 900 shows speckle 430 due to nuclear radiation throughout the image. The filtering process looks at a single pixel location, such as the pixel location at the center of circle 940, and creates a statistical distribution created from multiple images over time. From the image, a sample distribution is collected. For example, the sample distribution may be generated from pixels within circle 940. This sample distribution may include the pixel at the center of circle 940 and pixels surrounding the central pixel. The sample distribution is then compared to the statistical distribution. If the sample distribution deviates from the majority of the statistical distribution, speckle is likely within the same pixel distribution. For example, the sample distribution may deviate by two standard deviations from the statistical distribution. By examining the distribution of sample distributions and replacing pixels with high pixel brightness values with pixels closer to the mean of the sample distribution, where the bright pixels are removed from the mean, speckle can be removed. In another example, the mean of a statistical distribution may be used to replace bright pixels. Many approaches can be used to determine which pixels to replace bright pixels, such as using the median of a sample or statistical distribution. For brevity, not all approaches are described. Ultimately, bright pixels are replaced with pixels that are close to the appropriate value, eliminating the speckle brightness. Each pixel location corresponds to a different statistical distribution, and by creating a sample distribution that is compared to the statistical distribution corresponding to each pixel location, speckle 430 is identified and removed, resulting in an image similar to image 500 in FIG. 5 .

[0056] A video processor, such as processor 130 or processor 320, may be configured to implement a digital filter. Various aspects of the digital filter may be implemented according to FIG. 10 , which shows a diagram 1000 illustrating a filtering process for removing speckle. In step 1002, video data from a camera in a nuclear radiation environment is received by the video processor. If the video data is analog video data, the video processor proceeds to step 1004, where the analog video data is converted to digital video data, and then proceeds to step 1006. If the video data is already digital video data, the video processor proceeds directly to step 1006. In step 1006, an image is selected from the video data by the video processor. Once an image is selected, the video processor then performs a filtering step 1050. The filtering step 1050 continues from step 1008 to step 1022, and ends when the entire image has been filtered.

[0057] In step 1008, the video processor calculates the luminance value of each pixel in the image. In step 1010, the video processor generates a statistical distribution for each pixel location in the image using previously recorded images in the video data prior to the selected image to be filtered. In other words, the video processor generates a statistical distribution for each pixel location in the image using previously recorded images. In step 1012, the video processor begins examining each pixel in the image by selecting an initial pixel in the image. In step 1014, the video processor generates a sample distribution from the selected pixel location. The sample distribution may include the pixel at the selected pixel location and its neighboring pixels. In step 1016, the video processor compares the sample distribution with the statistical distribution. In step 1018, the video processor checks whether the sample distribution deviates from a majority of the statistical distribution. For example, the video processor may check whether the sample distribution deviates from the standard deviation or two standard deviations of the statistical distribution. In another example, in step 1018, the video processor may check whether the sample distribution is substantially different from the statistical distribution. For example, the statistical distribution may be normal, or the sample distribution may be skewed.

[0058] If the sample distribution deviates from the statistical distribution, the video processor proceeds along the "yes" branch to step 1020. In step 1020, the video processor updates the selected pixel. In various examples, the selected pixel may be updated by replacing it with a pixel in the sample distribution that is closer to the mean of the sample distribution after removing the brightest pixel from the sample distribution. In another example, the mean of the pixels in the statistical distribution may be used to replace the selected pixel. Once the selected pixel has been updated, the video processor proceeds to step 1022. If the sample distribution does not deviate from the statistical distribution, the video processor proceeds directly from step 1018 to step 1022. In step 1022, the video processor checks whether all pixel positions have been selected. If pixel positions remain, the video processor proceeds along the "no" branch to step 1012 and executes each step up to step 1022. This process is repeated until all pixel positions have been selected. Once all pixel positions have been selected, the video processor proceeds along the "yes" branch to step 1024. In step 1024, the filtered image is sent to a user interface for viewing by an operator. The updated image shows that speckle caused by nuclear radiation has been significantly reduced, and in some cases completely eliminated. In various examples, the filtering process may be performed in real time, allowing the operator to view updated images from the camera in real time.

[0059] (example) Various aspects of the subject matter described herein are illustrated in the following numbered examples.

[0060] Example 1 - A video processor for removing interference due to nuclear radiation. The video processor includes a control circuit having a memory. The control circuit is configured to receive video data from a camera located in a nuclear radiation environment, identify a first image from the video data, calculate a first luminance value for a first pixel at a first pixel location in the first image, and identify a second image from the video data, the first image corresponding to a time earlier than the second image. The control circuit is further configured to calculate a second luminance value for a second pixel at a second pixel location in the second image, the first pixel location and the second pixel location being the same. The control circuit is further configured to compare the first luminance value with the second luminance value and, if the second luminance value is greater than the first luminance value, update the second image by replacing the second pixel in the second image with the first pixel.

[0061] Example 2 - The video processor of Example 1, wherein the control circuitry is communicatively connected to the user interface.

[0062] Example 3 - The video processor of Example 1 or Example 2, wherein the video data is analog video data, and the control circuitry is further configured to convert the analog video data to digital video data.

[0063] Example 4 - The video processor of Example 1, Example 2, or Example 3, wherein the first image and the second image are consecutive in time.

[0064] Example 5 - The video processor of Example 1, Example 2, or Example 3, wherein the first image and the second image are not consecutive in time, and the control circuitry is further configured to calculate a period of time during which interference due to nuclear radiation decreases, and wherein the second image occurs after the first image and at or after the period of time.

[0065] Example 6 - The video processor of Example 1, Example 2, Example 3, Example 4, or Example 5, wherein the control circuitry is further configured to determine luminance values for all remaining pixel locations in the first image and the second image and update the second image. Updating the second image includes comparing, while varying pixel locations, luminance values of pixels at those locations in the second image with luminance values of pixels at those locations in the first image, and replacing corresponding pixels in the second image with pixels in the first image if the luminance value of the pixel in the second image is greater than the pixel in the first image.

[0066] Example 7 - The video processor of Example 1, Example 2, Example 3, Example 4, Example 5, or Example 6, wherein the control circuitry is further configured to send the updated second image to the user interface.

[0067] Example 8 - The video processor of Example 1, Example 2, Example 3, Example 4, Example 5, Example 6, or Example 7, wherein the control circuitry is further configured to calculate a third luminance value for a third pixel at a third pixel location in the updated second image and identify a third image from the video data, the second image corresponding to a time earlier than the third image. The control circuitry is further configured to calculate a fourth luminance value for a fourth pixel at a fourth pixel location in the third image, the third pixel location and the fourth pixel location being the same. The control circuitry is further configured to compare the third luminance value to the fourth luminance value and, if the fourth luminance value is greater than the third luminance value, update the third image by replacing the fourth pixel in the third image with the third pixel.

[0068] Example 9 - The video processor of Example 1, Example 2, Example 3, Example 4, Example 5, Example 6, Example 7, or Example 8, wherein the control circuitry is further configured to account for camera motion between the first image and the second image by receiving data indicative of camera motion, determining camera motion between the first image and the second image, and adjusting the second pixel positions based on the camera motion.

[0069] Example 10 - A video processor for removing interference due to nuclear radiation. The video processor includes a control circuit having a memory. The control circuit is configured to receive a first image from a camera located in a nuclear radioactive environment and a second image from the camera, the first image corresponding to a time earlier than the second image, calculate first brightness value data for the first image including brightness values for each pixel in the first image, and calculate second brightness value data for the second image including brightness values for each pixel in the second image. The control circuit is further configured to compare the first brightness data with the second brightness data, where the brightness value of each pixel at a pixel location in the first image is compared with the brightness value of a corresponding pixel at the same location in the second image. The control circuit is further configured to update the second image by replacing pixels in the second image with corresponding pixels in the first image based on the comparison of the first brightness data with the second brightness data.

[0070] Example 11 - The video processor of Example 10, wherein replacing pixels in the second image with corresponding pixels in the first image includes replacing pixels in the second image with pixels in the first image when a luminance value of the pixel in the second image is higher than a luminance value of the pixel in the first image while changing pixel positions in the second image.

[0071] Example 12 - The video processor of Example 10 or Example 11, wherein the control circuitry is further configured to send the updated second image to the user interface.

[0072] Example 13 - The video processor of Example 10, Example 11, or Example 12, wherein the first image and the second image are consecutive in time.

[0073] Example 14 - The video processor of Example 10, Example 11, or Example 12, wherein the first image and the second image are not consecutive in time, and the control circuitry is further configured to identify a period of time during which interference due to nuclear radiation is reduced, and the second image occurs after the first image and after the period of time.

[0074] Example 15 - The video processor of Example 10, Example 11, Example 12, Example 13, or Example 14, wherein the control circuitry is further configured to account for the camera motion between the first image and the second image by receiving data indicative of camera motion, determining camera motion between the first image and the second image, and adjusting the second pixel positions based on the camera motion.

[0075] Example 16 - A video processor for removing interference due to nuclear radiation, comprising a control circuit with a memory, the control circuit configured to receive video data from a camera located in a nuclear radiation environment, receive data indicative of camera movement, segment the video data into a plurality of consecutive images, and filter the interference due to nuclear radiation from each of the plurality of consecutive images to form an updated plurality of consecutive images. The filtering includes calculating first brightness value data for a first image, the first brightness value data including a brightness value of each pixel in the first image. The filtering further includes calculating second brightness value data for a second image, the second image following the first image, the second brightness value data including a brightness value of each pixel in the second image. The filtering further includes comparing the first brightness data and the second brightness data, wherein the brightness value of each pixel in the first image is compared to the brightness value of a pixel at a corresponding pixel location in the second image. The filtering further includes updating the second image by replacing pixels in the second image with corresponding pixels in the first image based on a comparison of the first luminance data and the second luminance data, and calculating third luminance value data for a third image, the third image following the second image, the third luminance value data including luminance values of each pixel in the third image. The filtering further includes comparing the second luminance data and the third luminance data, where the luminance value of each pixel in the second image is compared with the luminance value of a pixel at a corresponding pixel location in the third image, updating the third image by replacing pixels in the third image with corresponding pixels in the second image based on a comparison of the second luminance data and the third luminance data, and combining the multiple updated images into updated video data.

[0076] Example 17 - The video processor of Example 16, wherein the control circuitry is further configured to send updated video data to the user interface.

[0077] Example 18 - The video processor of Example 16 or Example 17, wherein the video data is analog video data, and the control circuitry is further configured to convert the analog video data to digital video data.

[0078] Example 19 - The video processor of Example 16, Example 17, or Example 18, wherein the control circuitry is further configured to receive data indicative of camera motion, identify camera motion between each of the plurality of sequential images, and account for camera motion between each of the plurality of sequential images by adjusting pixel positions during comparison of pixel intensities based on the camera motion.

[0079] Example 20 - The video processor of Example 16, Example 17, Example 18, or Example 19, wherein the video data is received in real time and the updated video data is transmitted in real time with a delay less than the length of the video data packet.

[0080] While several embodiments have been illustrated and described, the applicant does not intend to restrict or limit the scope of the appended claims to such details. Numerous modifications, variations, changes, substitutions, combinations, and equivalents may be made to these embodiments and will occur to those skilled in the art without departing from the scope of the present disclosure. Furthermore, the structure of each element of the described embodiments may be alternatively described as a means for providing the function provided by that element. Also, where materials are disclosed for particular components, other materials may be used. It is therefore to be understood that the foregoing description and the appended claims are intended to cover all such modifications, combinations, and variations as fall within the scope of the disclosed embodiments. The appended claims are intended to cover all such modifications, variations, changes, substitutions, variations, and equivalents.

[0081] Those skilled in the art will recognize that, generally, the terms used herein, and particularly in the appended claims (e.g., the body of the appended claims), are generally intended to be “open” terms (e.g., the term “comprising” should be interpreted as “including, but not limited to,” the term “having” should be interpreted as “having at least,” the term “including” should be interpreted as “including, but not limited to,” etc.). Those skilled in the art will further understand that where a specific number is intended in the introduced claim recitation, such intention will be expressly set forth in the claim; in the absence of such recitation, no such intention exists. For example, as an aid to understanding, the appended claims may include the introductory phrases “at least one” and “one or more” to introduce the claim recitation. However, the use of such phrases should not be construed to mean that a claim recitation introduced by the indefinite article "a" or "an" limits a particular claim containing such an introduced claim recitation to claims containing only one such recitation, even if that same claim includes the introductory phrase "one or more" or "at least one" and the indefinite article "a" or "an" (e.g., "a" and / or "an" should ordinarily be construed to mean "at least one" or "one or more"). The same is true with respect to the use of definite articles used to introduce claim recitations.

[0082] Additionally, even when a specific number in an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such a recitation should typically be interpreted to mean at least the recited number (e.g., the recitation of "two" alone, without any other modifier, typically means at least two, or more than two). Furthermore, when phrases similar to "at least one of A, B, and C, etc." are used, such a configuration is generally intended in the sense that those skilled in the art would understand the phrase (e.g., "a system having at least one of A, B, and C" includes, but is not limited to, a system having only A, a system having only B, a system having only C, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.). Those skilled in the art will further recognize that disjunctions and / or phrases presenting two or more alternative terms in the specification, claims, or drawings typically should be understood to contemplate the possibility of including one of the phrases, either of the phrases, or both phrases, unless otherwise specified. For example, the phrase "A or B" is generally understood to include the possibilities of "A" or "B" or "A and B."

[0083] With respect to the appended claims, those skilled in the art will understand that the operations described therein may generally be performed in any order. Also, while various operational flow diagrams are shown in a sequence, it should be understood that various operations may be performed in orders other than those shown, or may be performed simultaneously. Examples of such alternative orders include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, concurrent, reversed, or other variations, unless otherwise indicated. Furthermore, the use of terms such as "according to," "with respect to," or other past tense adjectives is not generally intended to exclude such variations, unless otherwise indicated.

[0084] It should be noted that terms such as "one embodiment," "an embodiment," "an example," "one example," etc., mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment. Thus, the appearances of the phrases "in one embodiment," "in an embodiment," "in one example," and "in one example" in various places throughout this specification do not necessarily all refer to the same embodiment. Furthermore, particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0085] Any patent applications, patents, non-patent publications, or other disclosure materials referred to herein and / or set forth in an Application Data Sheet are incorporated herein by reference to the extent that such material does not contradict this specification. Therefore, to the extent necessary, the disclosure expressly set forth herein supersedes any conflicting material incorporated herein by reference. Any material, or portion thereof, purportedly incorporated herein by reference that contradicts any existing definitions, statements, or other disclosure material set forth herein is incorporated only to the extent that there is no contradiction between the incorporated material and the existing disclosure material.

[0086] In summary, numerous advantages have been described by employing the concepts described herein. The foregoing description of one or more embodiments has been presented for purposes of illustration and description. It is not intended to be exhaustive or to be limited to the precise form disclosed. Modifications and variations are possible in light of the above teachings. The one or more embodiments have been selected to illustrate principles and practical applications, and have been described so as to enable those skilled in the art to utilize, with various modifications, various embodiments suited to the particular use contemplated. It is intended that the claims appended hereto define the overall scope.

Claims

1. 1. A video processor for removing interference due to nuclear radiation, comprising: a control circuit having a memory; The control circuit It receives video data from cameras placed in a nuclear radiation environment, Identifying a first image from the video data; calculating a first luminance value at a first pixel at a first pixel location in the first image; identifying a second image from the video data, the first image corresponding to a time earlier than the second image; calculating a second luminance value at a second pixel at a second pixel location in the second image, the first pixel location and the second pixel location being the same location; comparing the first luminance value with the second luminance value; a video processor configured to update the second image by replacing the second pixel in the second image with the first pixel if the second luminance value is greater than the first luminance value.

2. The video processor of claim 1 , wherein the control circuitry is communicatively connected to a user interface.

3. the video data is analog video data; The video processor of claim 1 , wherein the control circuitry is further configured to convert the analog video data to digital video data.

4. 2. The video processor of claim 1, wherein the first image and the second image are consecutive in time.

5. the first image and the second image are not consecutive in time; the control circuitry is further configured to calculate a period of time during which interference due to nuclear radiation decreases; 2. The video processor of claim 1, wherein the second image occurs at or after the time period after the first image.

6. The control circuit determining luminance values for all remaining pixel locations in the first image and the second image; further configured to update the second image; Updating the second image includes: Varying pixel locations and comparing the luminance value of the pixel at that location in the second image with the luminance value of the pixel at that location in the first image; and replacing a corresponding pixel in the second image with the pixel in the first image if the luminance value of the pixel in the second image is greater than the pixel in the first image.

7. The video processor of claim 6 , wherein the control circuitry is further configured to transmit the updated second image to a user interface.

8. The control circuit calculating a third luminance value at a third pixel at a third pixel location in the second image; identifying a third image from the video data, the second image corresponding to a time earlier than the third image; calculating a fourth luminance value at a fourth pixel at a fourth pixel location in the third image, the third pixel location and the fourth pixel location being the same; comparing the third luminance value with the fourth luminance value; 2. The video processor of claim 1, further configured to update the third image by replacing the fourth pixel in the third image with the third pixel if the fourth luminance value is greater than the third luminance value.

9. The control circuit receiving data indicative of the camera's movement; determining the camera motion between the first image and the second image; 2. The video processor of claim 1, further configured to account for camera motion between the first image and the second image by adjusting the second pixel position based on the camera motion.

10. 1. A video processor for removing interference due to nuclear radiation, comprising: a control circuit having a memory; The control circuit receiving a first image from a camera located in a nuclear radiation environment; receiving a second image from the camera, the first image corresponding to a time earlier than the second image; calculating first luminance value data of the first image, the first luminance value data including a luminance value of each pixel in the first image; calculating second luminance value data of the second image, the second luminance value data including a luminance value of each pixel in the second image; comparing the first luminance data with the second luminance data, wherein a luminance value of each pixel at a pixel location in the first image is compared with a luminance value of a corresponding pixel at the same location in the second image; and updating the second image by replacing pixels in the second image with corresponding pixels in the first image based on a comparison of the first luminance data and the second luminance data.

11. 11. The video processor of claim 10, wherein replacing pixels in the second image with corresponding pixels in the first image includes replacing pixels in the second image with pixels in the first image if a luminance value of the pixel in the second image is higher than a luminance value of the pixel in the first image while changing pixel positions in the second image.

12. The video processor of claim 10 , wherein the control circuitry is further configured to transmit the updated second image to a user interface.

13. 11. The video processor of claim 10, wherein the first image and the second image are consecutive in time.

14. the first image and the second image are not consecutive in time; the control circuitry is further configured to identify a period of time during which interference due to nuclear radiation is reduced; 11. The video processor of claim 10, wherein the second image occurs at or after the period of time after the first image.

15. The control circuit receiving data indicative of the camera's movement; determining the camera motion between the first image and the second image; 11. The video processor of claim 10, further configured to account for movement of the camera between the first image and the second image by adjusting the second pixel position based on the movement of the camera.

16. 1. A video processor for removing interference due to nuclear radiation, comprising: a control circuit having a memory; The control circuit It receives video data from cameras placed in a nuclear radiation environment, receiving data indicative of the camera's movement; Segmenting the video data into a plurality of successive images; configured to filter interference due to nuclear radiation from each of the plurality of sequential images to form an updated plurality of sequential images; The filtering may include: calculating first luminance value data for a first image, the first luminance value data including a luminance value for each pixel in the first image; calculating second luminance value data for a second image, the second image following the first image, the second luminance value data including a luminance value for each pixel in the second image; comparing the first luminance data with the second luminance data, wherein a luminance value of each pixel in the first image is compared with a luminance value of a pixel at a corresponding pixel location in the second image; updating the second image by replacing pixels in the second image with corresponding pixels in the first image based on a comparison of the first luminance data and the second luminance data; calculating third luminance value data of a third image, the third image following the second image, the third luminance value data including a luminance value of each pixel in the third image; comparing the second luminance data with the third luminance data, wherein a luminance value of each pixel in the second image is compared with a luminance value of a pixel at a corresponding pixel location in the third image; updating the third image by replacing pixels in the third image with corresponding pixels in the second image based on a comparison of the second luminance data and the third luminance data; and combining the plurality of updated images into updated video data.

17. The video processor of claim 16 , wherein the control circuitry is further configured to transmit the updated video data to a user interface.

18. the video data is analog video data; 17. The video processor of claim 16, wherein the control circuitry is further configured to convert the analog video data to digital video data.

19. The control circuit receiving data indicative of the camera's movement; determining a motion of the camera between each of the plurality of successive images; 17. The video processor of claim 16, further configured to account for the camera movement between each of the plurality of consecutive images by adjusting pixel positions during comparison of pixel intensities based on the camera movement.

20. the video data is received in real time; 17. The video processor of claim 16, wherein the updated video data is transmitted in real time with a delay less than the length of a video data packet.

Images