DETAILED ACTION
Response to Arguments
Applicant's arguments filed on 02/20/2026 have been fully considered but they are not persuasive.
Applicant’s argument: Bergen describes a applying a mask to reduce noise in at least one frame. (See, e.g., Gergen at Abstract.) Bergen, at paragraphs [0026], compares corresponding pixels from successive frames, and specifically that "if a value of 40 is at pixel location (0, 0) in frame t-1 and if a value of 20 is at pixel location (0, 0) in frame t, then the value of 20 will be selected by the minimum filter." As such, Bergen only selects values of pixels using a minimum filter, but does not update the second image by replacing the second pixel in the second image with the first pixel, as recited in claim 1. Additionally, Bergen goes on to describe using the minimum filter values in a difference threshold comparison at paragraph [0029], which further solidifies that Bergen does not teach any replacing of pixels based on the comparison of the two pixel brightness values as recited in claim 1. Therefore, Bergen does not teach or suggest, at least, updating a second image by replacing the second pixel in the second image with a first pixel when the second brightness value is greater than the first brightness value.
Examiner’s response: As explained the in the rejection of claim 1, Bergen discloses ¶26, “In block 205, a minimum filter picks the minimum value at each pixel by comparing corresponding pixels from successive frames, e.g., frames t-1 and t. Because there is some possibility that two noise impulses can overlap on successive frames, or that some other noise event will contaminate the minimum image, a 3-frame minimum may also used to achieve better noise suppression. For example, if a value of 40 is at pixel location (0, 0) in frame t-1 and if a value of 20 is at pixel location (0, 0) in frame t, then the value of 20 will be selected by the minimum filter.”
This is interpreted as follows: In the case of filtering with only two frames, the first image is the image at time t-1, and the second image is the image at time t. Therefore, for a minimum value filter when the first image pixel brightness value is less than the second image pixel brightness value, the output at time t for the second image is replaced by the first image pixels brightness value. When the second image pixel brightness value is smaller than the first image pixel brightness, then it remains the same. Further see Fig. 2 which shows the outputs are taken at time t so that means when the first image pixel brightness value is the minimum, it replaces the second image pixel brightness value.”
Therefore, the output of the minimum value filter is an image that contains all the original pixels from the image at time t, except for the values that have been replaced from image t-1 when p[t-1] (x, y) is the minimum value, or in other words p[t] (x, y) > p[t-1] (x, y). This is exactly the second image which has its values replaced, and in fact Bergen refers to this output in ¶28 as the minimum filter image, and is denoted in ¶29 as Min (x, y).
The additional processing such as masking done by Bergen in ¶29 and in Fig. 2 after the minimum filtering is completely optional and is not necessarily used as part of the combination of references. The output at 240 in Fig. 2 would be an image with impulse noise removed, but again this is completely optional, and the minimum filter image obtained from the minimum value filter prior to the rest of the steps shown in Fig. 2 teaches the filtering limitations of the claim.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, 6, 8-11, 13, 15-16, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation] in view of Bergen et al. (US Pub. No. 2006/0109903 A1) and in further view of Tanner et al. (US Pub. No. 2018/0286101 A1).
Regarding claim 1, Deng discloses, removing interference due to nuclear radiation, receive video data from a camera placed in a nuclear radioactive environment; (See Deng ¶43-45, “[0043] Please refer to Figure 1, which is a flow chart of a nuclear radiation detection method provided by an embodiment of the present invention. As can be seen from the figure, the nuclear radiation detection method includes the following steps: [0044] S10: Acquire continuous multi-frame images of the scene, and obtain a reference image based on the multi-frame images. The reference image is an image that suppresses the radiation response signal in the image. [0045] To obtain images of the on-site detection area, a series of continuous frame images of the site can be obtained by acquiring the video of the site. In practical applications, camera devices can be used to obtain on-site images.”)
Deng discloses denoising or filtering the video frames, see Deng ¶53, “After noise reduction processing, the image has no obvious noise” but Deng fails to disclose the limitations of this claim for filtering.
However, Bergen discloses, determine a first image from the video data;
calculate a first brightness value at a first pixel in a first pixel location in the first image;
determine a second image from the video data, wherein the first image corresponds to a time before the second image;
calculate a second brightness value at a second pixel in a second pixel location in the second image, wherein the first pixel location and the second pixel location are the same location;
compare the first brightness value to the second brightness value; and update the second image by replacing the second pixel in the second image with the first pixel when the second brightness value is greater than the first brightness value.
(See Bergen ¶26, “In block 205, a minimum filter picks the minimum value at each pixel by comparing corresponding pixels from successive frames, e.g., frames t-1 and t. Because there is some possibility that two noise impulses can overlap on successive frames, or that some other noise event will contaminate the minimum image, a 3-frame minimum may also used to achieve better noise suppression. For example, if a value of 40 is at pixel location (0, 0) in frame t-1 and if a value of 20 is at pixel location (0, 0) in frame t, then the value of 20 will be selected by the minimum filter.” Further see Bergen ¶28, “In block 210, the minimum filter image.”
This is interpreted as follows: In the case of filtering with only two frames, the first image is the image at time t-1, and the second image is the image at time t. Therefore, for a minimum value filter when the first image pixel brightness value is less than the second image pixel brightness value, the output at time t for the second image is replaced by the first image pixels brightness value. When the second image pixel brightness value is smaller than the first image pixel brightness, then it remains the same.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the minimum value filtering of sequential video images to remove speckle noise as suggested by Bergen for Deng’s filtering of nuclear radiation video images that contain noise. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a minimum value interframe filtering is highly effective at eliminating bright artifacts due to speckle noise, it preserves dark images features, it is computationally efficient, effective in state scenes, and retains sharp edges in dark areas.
Deng and Bergen disclose the above limitations but they fail to disclose the use of a video processor.
However Tanner discloses, a video processor comprising a control circuit that comprises a memory, wherein the control circuit is configured to: (See Tanner ¶153, “The exemplary integrated circuit includes one or more application processors 1205 (e.g., CPUs), at least one graphics processor 1210, and may additionally include an image processor 1215 and/or a video processor … The integrated circuit includes peripheral or bus logic including a USB controller 1225, universal asynchronous receiver/transmitter (UART) controller 1230, a serial peripheral interface (SPI)/secure digital input output (SDIO) controller 1235, and an integrated interchip sound (I2S)/inter-integrated circuit (I2C) controller 1240. … Memory interface may be provided via a memory controller 1265 for access to SDRAM or SRAM memory devices.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the video processor as suggested by Tanner to Deng and Bergen’s filtering of video. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a dedicated video processor is optimized for handling video signals efficiently, leading to a more polished final product with better color, contrast, and detail compared to general-purpose processors.
Regarding claim 4, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, wherein the first image and second image are sequential in time. (See Bergen ¶26, “In block 205, a minimum filter picks the minimum value at each pixel by comparing corresponding pixels from successive frames, e.g., frames t-1 and t.”)
Regarding claim 6, Deng, Bergen, and Tanner disclose, the video processor of claim 1, but they fail to disclose the limitations of this claim.
However, Deng discloses, wherein the control circuit is further configured to:
determine a brightness value for all remaining pixel locations in the first image and the second image; and update the second image, wherein updating the second image comprises: cycling through each pixel location and comparing the brightness value for a pixel at that location in the second image to the brightness value of a pixel at that location in the first image; and replacing the corresponding pixel in the second image with the pixel from the first image when the brightness value of the pixel in the second image is greater than the pixel in the first image. (See Deng ¶51, “Through the above process, each pixel of the i-th frame image is processed in turn to obtain the i-th frame image after replacement.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the filtering of each pixel of the image “in turn” or one after another as suggested by Deng to Deng, Bergen, and Tanner’s minimum value filtering of noise from video frames. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because it provides granular control since cycling through the pixels provides direct access to individual pixels, allowing for precise manipulation of each pixel's value based on its specific properties or its relationship to neighboring pixels.
Regarding claim 8, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, wherein the control circuit is further configured to:
calculate a third brightness value at a third pixel in a third pixel location in the second image;
determine a third image from the video data, wherein the second image corresponds to a time before the third image; calculate a fourth brightness value at a fourth pixel in a fourth pixel location in the third image, wherein the third pixel location and the fourth pixel location are the same;
compare the third brightness value to the fourth brightness value; and update the third image by replacing the fourth pixel in the third image with the third pixel when the fourth brightness value is greater than the third brightness value.
(See Bergen ¶18, “Impulse noise reduction block 105 uses the received IITV signal in order to remove impulse noise.” As shown in Fig. 2, a current frame and previous frame of the IITV sequence of frames is input to the minimum value filter. Since the sequence of frames are input to the filter, the first image is (t-1) and second image is (t) and they are filtered. When the next image (t+1) of the sequence of IITV is input, it is the third image and is now the new (t) and the second image that was input now becomes the new (t-1).)
Regarding claim 9, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, wherein the control circuit is further configured to: receive data indicative of movement of the camera; determine movement of the camera between the first image and the second image; (See Bergen ¶38, “Another problem with the minimum filter is due to image motion. Image motion (either global, due to camera motion, or local, due to object motion) interferes with the temporal comparison embodied in the minimum filter to produce undesirable results:” Further see Bergen ¶42, “FIG. 3 illustrates hierarchic block motion estimation in accordance with one embodiment of the present invention.”)
and account for movement of the camera between the first image and the second image by adjusting the second pixel location based on the movement of the camera. (See Bergen ¶42, “As explained above, temporal aligned images are essential in impulse noise reduction to output a clean image with fewer artifacts and better preservation of image features. There are a variety of motion estimation algorithms that can be used for image alignment of the previous frames to the current image.”)
Regarding claim 10, Deng discloses, removing interference due to nuclear radiation, receive a first image from a camera placed in a nuclear radioactive environment (See Deng ¶43-45, “[0043] Please refer to Figure 1, which is a flow chart of a nuclear radiation detection method provided by an embodiment of the present invention. As can be seen from the figure, the nuclear radiation detection method includes the following steps: [0044] S10: Acquire continuous multi-frame images of the scene, and obtain a reference image based on the multi-frame images. The reference image is an image that suppresses the radiation response signal in the image. [0045] To obtain images of the on-site detection area, a series of continuous frame images of the site can be obtained by acquiring the video of the site. In practical applications, camera devices can be used to obtain on-site images.”)
Deng discloses denoising or filtering the video frames, see Deng ¶53, “After noise reduction processing, the image has no obvious noise” but Deng fails to disclose the limitations of this claim for filtering.
However, Bergen discloses, receive a first image from a camera
receive a second image from the camera, wherein the first image corresponds to a time before the second image;
calculate first brightness value data for the first image, wherein the first brightness value data comprises the brightness value for each pixel in the first image;
calculate second brightness value data for the second image, wherein the second brightness value data comprises the brightness value for each pixel in the second image;
compare the first brightness data to the second brightness data, wherein the brightness value for each pixel at a pixel location in the first image is compared to the brightness value of the corresponding pixel at the same location in the second image;
and update the second image by replacing the pixels in the second image with the corresponding pixels in the first image based on the comparison of the first brightness data to the second brightness data.
(See Bergen ¶26, “In block 205, a minimum filter picks the minimum value at each pixel by comparing corresponding pixels from successive frames, e.g., frames t-1 and t. Because there is some possibility that two noise impulses can overlap on successive frames, or that some other noise event will contaminate the minimum image, a 3-frame minimum may also used to achieve better noise suppression. For example, if a value of 40 is at pixel location (0, 0) in frame t-1 and if a value of 20 is at pixel location (0, 0) in frame t, then the value of 20 will be selected by the minimum filter.” Further see Bergen ¶28, “In block 210, the minimum filter image.”
This is interpreted as follows: In the case of filtering with only two frames, the first image comprised of pixels brightness values is the image at time t-1, and the second image comprised of pixel brightness values is the image at time t. Therefore, for a minimum value filter when a first image pixel is less than a second image pixel, the output pixel value at time t for the second image is replaced by the first image pixels value. When the second image pixel value is smaller than the first image pixel, then it remains the same.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the minimum value filtering of sequential video images to remove speckle noise as suggested by Bergen for Deng’s filtering of nuclear radiation video images that contain noise. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a minimum value interframe filtering is highly effective at eliminating bright artifacts due to speckle noise, it preserves dark images features, it is computationally efficient, effective in state scenes, and retains sharp edges in dark areas.
Deng and Bergen disclose the above limitations but they fail to disclose the use of a video processor.
However Tanner discloses, a video processor comprising a control circuit that comprises a memory, wherein the control circuit is configured to: (See Tanner ¶153, “The exemplary integrated circuit includes one or more application processors 1205 (e.g., CPUs), at least one graphics processor 1210, and may additionally include an image processor 1215 and/or a video processor … The integrated circuit includes peripheral or bus logic including a USB controller 1225, universal asynchronous receiver/transmitter (UART) controller 1230, a serial peripheral interface (SPI)/secure digital input output (SDIO) controller 1235, and an integrated interchip sound (I2S)/inter-integrated circuit (I2C) controller 1240.
… Memory interface may be provided via a memory controller 1265 for access to SDRAM or SRAM memory devices.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the video processor as suggested by Tanner to Deng and Bergen’s filtering of video. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a dedicated video processor is optimized for handling video signals efficiently, leading to a more polished final product with better color, contrast, and detail compared to general-purpose processors.
Regarding claim 11, Deng, Bergen, and Tanner disclose, the video processor of Claim 10, wherein replacing the pixels in the second image with the corresponding pixels in the first image comprises cycling through each pixel location in the second image and replacing a pixel in the second image with a pixel in a first image when the brightness value of the pixel in the second image is higher than the brightness value of the pixel in the first image. (See the rejection of claim 6 as it is equally applicable for claim 11 as well.)
Regarding claim 13, Deng, Bergen, and Tanner disclose, the video processor of Claim 10, wherein the first image and second image are sequential in time. (See the rejection of claim 4 as it is equally applicable for claim 12 as well.)
Regarding claim 15, Deng, Bergen, and Tanner disclose, the video processor of Claim 10, wherein the control circuit is further configured to: receive data indicative of movement of the camera; determine movement of the camera between the first image and the second image; and account for movement of the camera between the first image and the second image by adjusting the second pixel location based on the movement of the camera. (See the rejection of claim 9 as it is equally applicable for claim 15 as well.)
Regarding claim 16, Deng discloses, removing interference due to nuclear radiation, receive video data from a camera placed in a nuclear radioactive environment; filter out interference due to nuclear radiation (See Deng ¶43-45, “[0043] Please refer to Figure 1, which is a flow chart of a nuclear radiation detection method provided by an embodiment of the present invention. As can be seen from the figure, the nuclear radiation detection method includes the following steps: [0044] S10: Acquire continuous multi-frame images of the scene, and obtain a reference image based on the multi-frame images. The reference image is an image that suppresses the radiation response signal in the image. [0045] To obtain images of the on-site detection area, a series of continuous frame images of the site can be obtained by acquiring the video of the site. In practical applications, camera devices can be used to obtain on-site images.”)
Deng discloses denoising or filtering the video frames, see Deng ¶53, “After noise reduction processing, the image has no obvious noise” but he fails to disclose the limitations of this claim for filtering.
However, Bergen discloses, receive data indicative of movement of the camera; (See Bergen ¶38, “Another problem with the minimum filter is due to image motion. Image motion (either global, due to camera motion, or local, due to object motion) interferes with the temporal comparison embodied in the minimum filter to produce undesirable results:” Further see Bergen ¶42, “FIG. 3 illustrates hierarchic block motion estimation in accordance with one embodiment of the present invention.”)
break the video data into a plurality of sequential images; (See Bergen ¶8, “The present invention generally relates to a method and apparatus for reducing noise in at least one frame in an image sequence.”)
filter out interference from each of the plurality of sequential images to form an updated plurality of sequential images, wherein the filtering comprises:
calculate first brightness value data for a first image, wherein the first brightness value data comprises a brightness value for each pixel in the first image;
calculate second brightness value data for a second image, wherein the second image occurs sequentially after the first image, and wherein the second brightness value data comprises a brightness value for each pixel in the second image;
compare the first brightness data to the second brightness data, wherein the brightness value for each pixel in the first image is compared to the brightness value of a pixel located at a corresponding pixel location in the second image;
update the second image by replacing the pixels in the second image with the corresponding pixels in the first image based on the comparison of the first brightness data to the second brightness data;
(See Bergen ¶26, “In block 205, a minimum filter picks the minimum value at each pixel by comparing corresponding pixels from successive frames, e.g., frames t-1 and t. Because there is some possibility that two noise impulses can overlap on successive frames, or that some other noise event will contaminate the minimum image, a 3-frame minimum may also used to achieve better noise suppression. For example, if a value of 40 is at pixel location (0, 0) in frame t-1 and if a value of 20 is at pixel location (0, 0) in frame t, then the value of 20 will be selected by the minimum filter.” Further see Bergen ¶28, “In block 210, the minimum filter image.”
This is interpreted as follows: In the case of filtering with only two frames, the first image comprised of pixels brightness values is the image at time t-1, and the second image comprised of pixel brightness values is the image at time t. Therefore, for a minimum value filter when a first image pixel is less than a second image pixel, the output pixel value at time t for the second image is replaced by the first image pixels value. When the second image pixel value is smaller than the first image pixel, then it remains the same.)
calculate third brightness value data for a third image, wherein the third image occurs sequentially after the second image, and wherein the third brightness value data comprises a brightness value for each pixel in the third image;
compare the second brightness data to the third brightness data, wherein the brightness value for each pixel in the second image is compared to the brightness value of a pixel located at a corresponding pixel location in the third image;
update the third image by replacing the pixels in the third image with the corresponding pixels in the second image based on the comparison of the second brightness data to the third brightness data;
and combine the plurality of updated images into updated video data.
(See Bergen ¶18, “Impulse noise reduction block 105 uses the received IITV signal in order to remove impulse noise.” As shown in Fig. 2, a current frame and previous frame of the IITV sequence of frames is input to the minimum value filter. Since the sequence of frames are input to the filter, the first image is (t-1) and second image is (t) and they are filtered. When the next image (t+1) of the sequence of IITV is input, it is the third image and is now the new (t) and the second image that was input now becomes the new (t-1).)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the minimum value filtering of sequential video images to remove speckle noise as suggested by Bergen for Deng’s filtering of nuclear radiation video images that contain noise. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a minimum value interframe filtering is highly effective at eliminating bright artifacts due to speckle noise, it preserves dark images features, it is computationally efficient, effective in state scenes, and retains sharp edges in dark areas.
Deng and Bergen disclose the above limitations but they fail to disclose the use of a video processor.
However Tanner discloses, a video processor comprising a control circuit that comprises a memory, wherein the control circuit is configured to: (See Tanner ¶153, “The exemplary integrated circuit includes one or more application processors 1205 (e.g., CPUs), at least one graphics processor 1210, and may additionally include an image processor 1215 and/or a video processor … The integrated circuit includes peripheral or bus logic including a USB controller 1225, universal asynchronous receiver/transmitter (UART) controller 1230, a serial peripheral interface (SPI)/secure digital input output (SDIO) controller 1235, and an integrated interchip sound (I2S)/inter-integrated circuit (I2C) controller 1240.
… Memory interface may be provided via a memory controller 1265 for access to SDRAM or SRAM memory devices.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the video processor as suggested by Tanner to Deng and Bergen’s filtering of video. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because a dedicated video processor is optimized for handling video signals efficiently, leading to a more polished final product with better color, contrast, and detail compared to general-purpose processors.
Regarding claim 19, Deng, Bergen, and Tanner disclose, the video processor of Claim 16, wherein the control circuit is further configured to: receive data indicative of movement of the camera; determine movement of the camera between each of the plurality of sequential images; and account for movement of the camera between each of the plurality of sequential images by adjusting the pixel locations during pixel brightness comparison based on the movement of the camera. (See the rejection of claim 9 as it is equally applicable for claim 19 as well.)
Claims 2, 7, 12, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation] in view of Bergen et al. (US Pub. No. 2006/0109903 A1) Tanner et al. (US Pub. No. 2018/0286101 A1) in view of Nakahira et al. (US Pub. No. 2012/0026317 A1).
Regarding claim 2, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, but he fails to disclose the limitations of this claim.
However, Nakahira discloses, wherein the control circuit is communicably coupled to a user interface. (See Nakahira ¶157, “FIG. 18 represents an example of a screen output on the display upon inspection for displaying a deteriorated image 1801 (corresponding to the image 1420 shown in FIG. 14A), and a processing result 1802 after radiation noise removing (corresponding to the image 1430 shown in FIG. 14A). An interface for changing the display rate 1803, and an interface for setting the processing parameter in detail.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the user interface for denoising as suggested by Nakahira to Deng, Bergen, and Tanner’s noise filtering for nuclear radiation using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is in order that an operator can review and display inspection images.
Regarding claim 7, Deng, Bergen, and Tanner disclose, the video processor of Claim 6, but he fails to disclose the limitations of this claim.
However, Nakahira discloses, wherein the control circuit is further configured to: transmit the updated second image to a user interface. (See Nakahira ¶157, “FIG. 18 represents an example of a screen output on the display upon inspection for displaying a deteriorated image 1801 (corresponding to the image 1420 shown in FIG. 14A), and a processing result 1802 after radiation noise removing (corresponding to the image 1430 shown in FIG. 14A). An interface for changing the display rate 1803, and an interface for setting the processing parameter in detail.”)
The proposed combination of Deng, Bergen, and Tanner’s and Nakahira and the motivation presented in the rejection of claim 2 are equally applicable to claim 7 and are incorporated by reference.
Regarding claim 12, Deng, Bergen, Tanner, and Nakahira disclose, the video processor of Claim 10, wherein the control circuit is further configured to: transmit the updated second image to a user interface. (See the rejection of claim 7 as it is equally applicable for claim 12 as well.)
Regarding claim 17, Deng, Bergen, Tanner, and Nakahira disclose, the video processor of Claim 16, wherein the control circuit is further configured to: transmit the updated video data to a user interface. (See the rejection of claim 12 as it is equally applicable for claim 17 as well.)
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation]) in view of Bergen et al. (US Pub. No. 2006/0109903 A1) Tanner et al. (US Pub. No. 2018/0286101 A1) and in further view of Stenman (US Pub. No. 2013/0208129 A1).
Regarding claim 3, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, but he fails to disclose the limitations of this claim.
However, Stenman discloses, wherein the video data is analog video data and wherein the control circuit is further configured to convert the analog video data to digital video data. (See Stenman ¶37, “The image recording device 2 may also comprise an analogue camera and a converting device, whereby the converting device is configured to convert the analogue image into a digital image. The analogue camera and the conversion device may be physically separated.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the analog to digital conversion for video data as suggested by Stenman to Deng, Bergman, and Tanner’s denoising of videos frames. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is because digital signals may be amplified and regenerated without loss of quality.
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation]) Bergen et al. (US Pub. No. 2006/0109903 A1) Tanner et al. (US Pub. No. 2018/0286101 A1) and in further view of Pitcher (US Pub. No. 2017/0024878 A1).
Regarding claim 5, Deng, Bergen, and Tanner disclose, the video processor of Claim 1, but he fails to disclose the limitations of this claim.
However, Pitcher discloses, wherein the first image and second image are not sequential in time, wherein the control circuit is further configured to calculate an amount of time for interference due to nuclear radiation to reduce, and wherein the second image occurs at or after that amount of time after the first image. (See Pitcher ¶18, “Video capture card in computer 10 converts video signal 8 to digital video frames 22, 24, 26, 28, 30 (FIG. 4) at a specified frame rate. … Once a xnoid is detected, the xnoid and surrounding pixels are replaced with corresponding pixels in the same location from other frames. For each pixel marked as a xnoid in video frame 26, the pixel xnoid, and the surrounding pixel values are replaced with pixel intensity values in the same locations as frame 28. If replacement pixel of frame 28 has already been marked as a xnoid (or is a surrounding pixel of a xnoid) then the xnoid pixel and surrounding pixels of frame 26 are replaced with the pixels of frame 24, frame 30 or frame 22, respectively.” Whereby frames 26 and 22 are not sequentially adjacent.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the filtering using non-sequential frames as suggested by Pitcher to Deng, Bergen, and Tanner’s denoising of images. This can be done using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is in order to only use noise free images even if they are non-sequential.
Regarding claim 14, Deng, Bergen, Tanner, and Pitcher disclose, the video processor of Claim 10, wherein the first image and second image are not sequential in time, wherein the control circuit is further configured to determine an amount of time for interference due to nuclear radiation to reduce, and wherein the second image occurs at or after that amount of time after the first image. (See the rejection of claim 5 as it is equally applicable for claim 14 as well.)
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation]) in view of Nakahira et al. (US Pub. No. 2012/0026317 A1) Bergen et al. (US Pub. No. 2006/0109903 A1) Tanner et al. (US Pub. No. 2018/0286101 A1) and in further view of Stenman (US Pub. No. 2013/0208129 A1).
Regarding claim18, Deng, Bergen, Tanner, Nakahira, and Stenman disclose, the video processor of Claim 16, wherein the video data is analog video data and wherein the control circuit is further configured to convert the analog video data to digital video data. (See the rejection of claim 3 as it is equally applicable for claim 18 as well.)
The proposed combination of Deng, Bergen, and Tanner with Stenman and the motivation presented in the rejection of claim 3 are equally applicable to claim 18 and are incorporated by reference.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Deng et al. (CN 112505740 A1) [see English translation]) Bergen et al. (US Pub. No. 2006/0109903 A1) Tanner et al. (US Pub. No. 2018/0286101 A1) in view of Nakahira et al. (US Pub. No. 2012/0026317 A1) and in further view of Pitcher (US Pub. No. 2017/0024878 A1).
Regarding claim 20, Deng, Bergen, Tanner, and Nakahira disclose, the video processor of Claim 16, but they fail to disclose the limitations of this claim.
However, Pitcher discloses, 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 a video data packet. (See Pitcher ¶17, “With use of a computer equipped with a video capture card, the video can be captured, filtered and displayed in real-time with a delay of only a few frame times. Alternately, the video can be stored and then replayed from the captured digital file with a similar delay of zero to a few frame times.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the real-time filtering as suggested by Pitcher to Deng, Bergen, Tanner, and Nakahira’s denoising of images using known engineering techniques, with a reasonable expectation of success. The motivation for doing so is in order to avoid delays in displaying noise free images while a nuclear reactor is being inspected.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/DAVID PERLMAN/Primary Examiner, Art Unit 2673
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