DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/17/2026 was filed after the mailing date of the non-final on 04/07/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
Claims 1-20 were previously pending and subject to non-final action filed on 04/07/2026. In the response filed 07/07/2026, claims 1-4, 8-9, 14-17, 18-20 were amended, claims 6-7, 10 and 18 were canceled, and newly added claims 21-24 were amended. Therefore, claims 1-5, 8-9, 11-17 and 19-24 are currently pending and subject to the final action below.
Response to Arguments
Applicant’s arguments, see page 9, filed 07/07/2026, with respect to objection of the specification have been fully considered and are persuasive. The objection of the specification has been withdrawn.
Applicant’s arguments, see page 9, filed 07/07/2026, with respect to claims 9-10 under 35 U.S.C. 101 have been fully considered and are persuasive. The 101 rejection of claims 9-10 has been withdrawn.
Applicant’s arguments, see pages 9-13, filed on 07/07/2026 with respect to claims 1-17 under the prior rejections have been considered but are moot with respect to the prior rejection because 1-17 are currently rejected under 35 U.S.C. 103 set forth below.
Examiner Notes
Jaggies can also be referred to as “Stair-stepping”, “aliasing”, “Rasterization artifacts”, “Jagged edges/artifacts”, or “Spatial Aliasing”. Gaussian blur is a type of low-pass filter used in image processing. Gaussian blur can also be referred to as one-dimensional filter. Anti-aliasing or (filtering) is a technique used for correcting Jaggies in images/videos/pictures. A right-angle parallelogram is a rectangle shape or also called rhomb(i).
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.
Claim(s) 1, 5, 8-9, 17 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Guo (US 10410326 B2, Pub Date: Sep. 10, 2019) in view of KADRI (US 20170249742 A1, Pub Date: Aug. 31, 2017).
Regarding independent claim 1, Guo teaches: An image processing method, comprising: acquiring an intermediate image (Guo − [Col. 1, ll. 5-7] The present invention relates to the technical field of image and video processing,) wherein the intermediate image comprises jaggies; (Guo − [Col. 1, ll. 10-15] image and video processed has jagginess occur near edges)
wherein the direction has an association relationship with a shape of the jaggies. (Guo − FIG. 6 is a schematic drawing of directional filtering, wherein the black dots are original image pixels, P is the pixel to be filtered, and the coordinates of intersection points of a line Lp that goes through P along the edge direction and the horizontal scanning lines (H0, H1, H2, H3, H4 in FIG. 6) neighboring P are calculated according to the edge direction of the pixel P to be filtered, and temporary pixels (P0, P1, P2, P3, P4) at the intersection points, as indicated by the stars in FIG. 6, are interpolated by means of a horizontal interpolation method, then the pixel P is filtered by a one-dimensional filter using the temporary pixels along the edge direction to obtain the final directional filtering result.). horizontal orientation of the jaggies pixel to be filtered. Fig. 6 is a shape where jaggies occur.
determining a parameter corresponding to a one-dimensional blur processing according, the one-dimensional blur processing on the intermediate image in a direction to acquire an output image, (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction and outputs the directional filtering result (output image) [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;)
Guo teaches a one-dimensional blur processing but does not explicitly teach: to a blur degree of the intermediate image, wherein the parameter comprises at least one of a first blur radius or a first sampling step length; and performing, according to at least one of the first blur radius or the first sampling step length,
However, KADRI teaches: determining a parameter according to a blur degree of the intermediate image, (KADRI – [0055-0061] [0055] The degree of blur applied to a region of an image in dependence on the direction of capture of the camera sensor 102 may be considered to be some combination of one or more of the factors in the following non-exhaustive list: [0056] i. The maximum intensity of the blur in the blur region (e.g. a measure of blur radius).)
wherein the parameter comprises at least one of a first blur radius or a first sampling step length; (KADRI – [0064] Any suitable blur function or algorithm may be used. For example, Gaussian blur may be applied by processor 104, with a new value for each pixel or group of pixels in the blurred regions; [0065] The intensity of the blur applied to a pixel may be controlled by varying the size of the standard deviation, σ, which is an example of a blur radius. A larger standard deviation corresponds to a greater intensity of blur.)
and performing, according to at least one of the first blur radius or the first sampling step length, (KADRI – [0064] Any suitable blur function or algorithm may be used. For example, Gaussian blur may be applied by processor 104, with a new value for each pixel or group of pixels in the blurred regions; [0065] The intensity of the blur applied to a pixel may be controlled by varying the size of the standard deviation, σ, which is an example of a blur radius. A larger standard deviation corresponds to a greater intensity of blur.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the one-dimensional direction filtering of Guo to determine and use a blur radius according to a degree of blur, as taught by KADRI, in order to control the intensity of blur applied during image processing.
Regarding dependent claim 5, depends on claim 1, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding independent claim 8, is direct to an electronic device. Claim 8 have similar/same technical features/limitations as claim 1. Claim 8 is rejected under the same rationale.
Regarding independent claim 9, is direct to a non-transitory computer-readable storage medium. Claim 9 have similar/same technical features/limitations as claim 1. Claim 9 is rejected under the same rationale.
Regarding dependent claim 17, depends on claim 9, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding dependent claim 22, depends on claim 8, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Claim(s) 2-4, 11-16, 19-21, and 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over GUO and KADRI as applied to claim 1, 8 above, and further in view of ISO (US 20120250993 A1, Pub Date: Mar. 20, 2012).
Regarding dependent claim 2, depends on claim 1, Guo does not explicitly teach: the shape of the jaggies being a right-angled parallelogram
However, ISO teaches: wherein, in case of the shape of the jaggies being a right-angled parallelogram, the direction is any diagonal direction of the right-angled parallelogram. (ISO − [0029] FIG. 3 is a diagram illustrating occurrence of jaggedness as a problem of the pixel number reduction process;) Fig. 3 illustrate rectangular jaggies in image pixelation.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 3, depends on claim 1, Guo teaches: wherein, the performing the one-dimensional blur processing on the immediate image in the direction to acquire the output image, comprises: and a convolution kernel corresponding to the one-dimensional blur processing. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter along the edge direction
Guo does not explicitly teach: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length;
However, ISO teaches: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
acquiring a pixel value of the center pixel point and pixel values of surrounding pixel points for each step of the blur processing, wherein the surrounding pixel points comprise pixel points along the direction within the first blur radius centered on the center pixel point; (ISO − [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
and acquiring a value of a center pixel point in the output image by calculating according to the pixel value of the center pixel point, the pixel values of the surrounding pixel points, (ISO − [0012] [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 4, depends on claim 3, Guo does not explicitly teach: wherein, the acquiring the pixel value of the center pixel point and the pixel values of surrounding pixel points for each step of the blur processing, comprises:
However, ISO teaches: wherein, the acquiring the pixel value of the center pixel point and the pixel values of surrounding pixel points for each step of the blur processing, comprises: determining the pixel points along the direction within the first blur radius centered on the center pixel point as candidate pixel points for each center pixel point; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
determining the surrounding pixel points from the candidate pixel points according to an amount relationship between a preset threshold value and each element in the convolution kernel; (ISO − [0213] [0220] The blending process unit 105 computes, for the luminance high frequency component information 84 input from the edge extraction unit 104, a blending rate according to the luminance high frequency component information in each pixel unit based on a weight (blending rate) distribution function that linearly changes threshold values using the upper-limit threshold value (th.sub.upper) and the lower-limit threshold value (th.sub.lower) that are determined in advance.)
and acquiring the pixel value of the center pixel point and the pixel values of the surrounding pixel points. (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 11, depends on claim 2, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding dependent claim 12, depends on claim 3, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding dependent claim 13, depends on claim 4, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding dependent claim 14, depends on claim 9, Guo does not explicitly teach: the shape of the jaggies being a right-angled parallelogram
However, ISO teaches: wherein, in case of the shape of the jaggies being a right-angled parallelogram, the direction is any diagonal direction of the right-angled parallelogram. (ISO − [0029] FIG. 3 is a diagram illustrating occurrence of jaggedness as a problem of the pixel number reduction process;) Fig. 3 illustrate rectangular jaggies in image pixelation.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 15, depends on claim 9, Guo teaches: wherein the performing the one-dimensional blur processing on the intermediate image in the direction to acquire the output image, comprises: and a convolution kernel corresponding to the one-dimensional blur processing. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction (direction) and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter along the edge direction
Guo does not explicitly teach: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length;
However, ISO teaches: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
acquiring a pixel value of the center pixel point and pixel values of surrounding pixel points for each step of the blur processing, wherein the surrounding pixel points comprise pixel points along the direction within the first blur radius centered on the center pixel point; (ISO − [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
acquiring a value of a center pixel point in the output image by calculating according to the pixel value of the center pixel point, the pixel values of the surrounding pixel points, (ISO − [0012] [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 16, depends on claim 15, Guo does not explicitly teach: determining the pixel points along the direction within the first blur radius centered on the center pixel point as candidate pixel points for each center pixel point;
However, ISO teaches: acquiring the pixel value of the center pixel point and the pixel values of surrounding pixel points for each step of the blur processing, comprises:
wherein the processing module is further configured to: determining the pixel points along the direction within the first blur radius centered on the center pixel point as candidate pixel points for each center pixel point; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
determining the surrounding pixel points from the candidate pixel points according to an amount relationship between a preset threshold value and each element in the convolution kernel; (ISO − [0213] [0220] The blending process unit 105 computes, for the luminance high frequency component information 84 input from the edge extraction unit 104, a blending rate according to the luminance high frequency component information in each pixel unit based on a weight (blending rate) distribution function that linearly changes threshold values using the upper-limit threshold value (th.sub.upper) and the lower-limit threshold value (th.sub.lower) that are determined in advance.)
and acquiring the pixel value of the center pixel point and the pixel values of the surrounding pixel points. (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 19, depends on claim 8, Guo does not explicitly teach: the shape of the jaggies being a right-angled parallelogram
However, ISO teaches: wherein, in case of the shape of the jaggies being a right-angled parallelogram, the direction is any diagonal direction of the right-angled parallelogram. (ISO − [0029] FIG. 3 is a diagram illustrating occurrence of jaggedness as a problem of the pixel number reduction process;) Fig. 3 illustrate rectangular jaggies in image pixelation.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 20, depends on claim 8, Guo teaches: a wherein, the performing the one- dimensional blur processing on the immediate image to be processed in the direction to acquire the output image, comprises: (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter along the edge direction
Guo does not explicitly teach: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length;
However, ISO teaches: determining a center pixel point corresponding to each step of the blur processing according to the first sampling step length; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
acquiring a pixel value of the center pixel point and pixel values of surrounding pixel points for each step of the blur processing, wherein the surrounding pixel points comprise pixel points along the direction within the first blur radius centered on the center pixel point; (ISO − [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
and acquiring a value of a center pixel point in the output image by calculating according to the pixel value of the center pixel point, the pixel values of the surrounding pixel points, (ISO − [0012] [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 21, depends on claim 20, Guo does not explicitly teach: wherein, the acquiring the pixel value of the center pixel point and the pixel values of surrounding pixel points for each step of the blur processing, comprises:
However, ISO teaches: wherein, the acquiring the pixel value of the center pixel point and the pixel values of surrounding pixel points for each step of the blur processing, comprises: determining the pixel points along the direction within the first blur radius centered on the center pixel point as candidate pixel points for each center pixel point; (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
determining the surrounding pixel points from the candidate pixel points according to an amount relationship between a preset threshold value and each element in the convolution kernel; (ISO − [0213] [0220] The blending process unit 105 computes, for the luminance high frequency component information 84 input from the edge extraction unit 104, a blending rate according to the luminance high frequency component information in each pixel unit based on a weight (blending rate) distribution function that linearly changes threshold values using the upper-limit threshold value (th.sub.upper) and the lower-limit threshold value (th.sub.lower) that are determined in advance.)
and acquiring the pixel value of the center pixel point and the pixel values of the surrounding pixel points. (ISO − [0012] [0055-0059] Fig 1A/1B, a Gb pixel center, and surrounding pixels of the jaggedness-occurring image. [0055-0059] [0136-0140] Next, (A) a pixel value x of a noted position (i, j) in the image prior to the jaggedness occurrence and (B) pixel values y1, y2, . . . , yn of the n peripheral pixels in the position (i, j) in the image after the jaggedness occurrence are respectively observed.)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teaching of Guo, and ISO as each invention in the same field of image processing and filtering out noise within an imagery. One of ordinary skill in the art would have been motivated to make these modification to improve accuracy of which pixel calculated in adjusting and reducing jaggies in image processing (0009).
Regarding dependent claim 23, depends on claim 19, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Regarding dependent claim 24, depends on claim 20, Guo teaches: wherein the one-dimensional blur processing is any one selected from a group consisting of Gaussian blur, median blur and mean blur. (Guo − [Col. 1 ll. 62-67] filters the pixel to be filtered by a one-dimensional filter using the temporary pixels along the edge direction and outputs the directional filtering result. [Col. 2 ll. 60-65] FIG. 6 is a schematic drawing of directional filtering according to the present invention;) filtering by a one-dimensional filter is Gaussian blur
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CARL E BARNES JR whose telephone number is (571)270-3395. The examiner can normally be reached Monday-Friday 9am-6pm.
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/CARL E BARNES JR/Examiner, Art Unit 2178
/STEPHEN S HONG/Supervisory Patent Examiner, Art Unit 2178
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