DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Such claim limitations include, for example, In claim 1:
conversion unit,
calculation unit,
correction unit,
inverse-conversion unit, and
synthesis unit.
In claim 6:
correction gain calculation unit, and
correction unit.
In claim 7:
calculation unit, and
correction unit.
In claims 8-9:
correction gain calculation unit, and
correction unit.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 6 and 10 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by ADCOCK et al., (US Patent No 10,009,551)
Regarding claim 1: ADCOCK teaches: A synthetic image generation system [Figs. 1 and 2; and claim 4, Col. 1 line 50 teaches: In an image processing system; Col. 2 line 63-67 teaches: An image processor 106 obtains…Image processor 106 might be part of an integrated system] for generating a synthetic image by synthesizing a first image captured by a first camera and a second image captured by a second camera [Figs. 1 and 3, Col. 1 line 24 teaches: FIG. 3 illustrates a stitched image generated a first input image and a second input image; claims 4 and 1 teach: generating the stitched image from the first modified image and the second modified image; Col. 4 line 21-22, Col. 2 line 28-46, Col. 1 line 51 teach that images are obtained from a plurality of cameras], at least a part of a field of view of the first camera and at least a part of a field of view of the second camera overlapping each other [Figs. 1 and 3, Col 2 line 60 teaches overlapping fields of view; and Col. 2 line 31-32 teach: This processing might include overlaps of images; Col. 4 line 7 teaches: there is an area of overlap], the synthetic image being an image in which at least a part of the first image and at least a part of the second image are joined together [Figs. 1, 3 and 9; Col. 4 lines 4-12 teach: FIG. 3 illustrates a stitched image 300 that might be generated by image processor 220 from a first input image 302 and a second input image 304; and Col. 12 line 4 teaches: stitching of two images], the synthetic image generation system comprising: a first image conversion unit configured to apply a predetermined image conversion to the first image to generate a post-conversion first image; a second image conversion unit configured to apply the predetermined image conversion to the second image to generate a post-conversion second image; [Col 5, line 38 teaches: two separate image signal processors; Fig. 5 teaches two image conversion units before the Texture Lookup blocks (i.e. before 518(1) and (2); in addition image conversion units are applied within the blocks 518(1) and 518(2]; a comparative image extracting unit [Fig. 8, col. 12 line 10 teaches: the overlap region can be cropped or ignored; and Col. 9 lines 19-21 teach: In step 801, the image processor compiles statistics for both cameras based on images from those cameras and determines the overlap region] configured to extract: a predetermined part or a portion of the predetermined part of the post-conversion first image for use as a first comparative image, the predetermined part of the post-conversion first image capturing the part of the field of view of the first camera overlapping the field of view of the second camera [claim 7, Col. 9 lines 21-28 teach: For the overlap region, the image processor calculates and stores a grid of subsampled average and variance statistics from both cameras after an alignment is done for the two images. Thus, the subsamples overlap from image to image and for a subsample, the average pixel value (this can be done on a color component by component basis) would be known for the same subsample of the scene for both cameras; and col. 10 line 12, col.10 lines 42-46, col. 10 lines 58-64 teach: the analysis can be done on sections of the overlap region each having multiple pixels therein, so that there are fewer data points than there are pixels in the overlap region. Preferably, the overlap region is divided into enough sections so that there are not too many artifacts]; and a predetermined part of the post-conversion second image for use as a second comparative image, the predetermined part of the post-conversion second image capturing a part of the field of view of the second camera that is same as that captured in the first comparative image [claim 7; and Col. 9 lines 23 teaches: from both cameras; Col. 10 lines 13-15 teach: splitting the overlap region into a small number of sections (such as four sections) and estimating the corrections; Col. 10 lines 42-44 teach: The pixels are from first region of the first image and a second region of the second image and correspond to portions of a view]; a correction gain calculation unit configured to calculate a ratio of a representative value among pixel values of the first comparative image to a representative value among pixel values of the second comparative image as a correction gain for the post-conversion second image [Fig. 8, claim 7, Col. 9 lines 19-28, col. 9 line 35 teaches: In step 803, the image processor computes the correction needed to remove uniformity issues indicated by the differences in the statistics between the two cameras; and Col. 11 lines 62-64 teach: While the overlap region might be divided into sections to obtain a data point per section, whether an offset, a factor, or other data point usable to generate a correction; and Col. 10 line 40-42 teach: In a general case, the pixels from the overlap region are analyzed by an image processor to extract some correction offsets, factors, or other types of corrections.]; a correction unit configured to correct the post-conversion second image based on the correction gain to generate a post-correction second image [Figs. 5 and 8, col. 5 line 4 teach: The lookup table can be used to apply gain in way that is equivalent to a change in exposure; Col. 10 lines 26-27 teach: In step 807, the image processor can apply the corrections as part of a GPU lookup process and/or texture]; a second image inverse-conversion unit configured to apply an inverse conversion of the predetermined image conversion to the post-correction second image to generate a post-inverse-conversion second image [Figs. 5 (e.g. blocks after gain block in 518(2)), Col. 6 lines 1-3 teach: reapplication of the gamma correction, and then reapplication of the RGB2YUV conversion]; and a synthesis unit configured to synthesize the post-inverse-conversion second image with the first image or with an image obtained by applying the inverse-conversion of the predetermined image conversion to the post-conversion first image, to generate a synthetic image [Fig. 5 (block 522) and Fig. 9, Col. 12 lines 4-5 teach: FIG. 9 illustrates stitching of two images as might be done by the image processor; and claims 4, 7 and 1 teach: generating the stitched image from the first modified image and the second modified image], wherein the predetermined image conversion is performed such that a ratio of a pixel value in the post-conversion first image, obtained from a first pixel value in the first image through the predetermined image conversion, to a pixel value in the post-conversion second image, obtained from a second pixel value in the second image through the predetermined image conversion, is closer to 1 than is a ratio of the first pixel value to the second pixel value [Col. 6 lines 50-52 teach: The image processor can efficiently blend between YUV images that have been processed with different image signal processor parameters, such as different gamma curves; and Col. 6, lines 12-22 teach: In some variations, the texture or the gain array provide for different gamma values over the images. For example, where a left image and a right image are to be stitched and there is a gain difference between the two images, there might be different lookup tables for the left and right halves of each of the left and right images, blended so that stitching seams are not visible. In such cases, the image processor might remove each camera image's gamma and apply the desired gamma that should occur at the seam. An example might be an average of the gammas of the left and right images. (i.e. one could average the camera's gammas of the images to be stitched, and use such average in all gamma blocks to partially correct the camera's gamma. This would therefore make the correction gain closer to 1.)].
Regarding claim 2: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein, in the predetermined image conversion, a range of pixel values is converted in the first image and in the second image such that at least a value that serves as a lower limit of the range of pixel values in the first image and the second image is larger than before the predetermined image conversion is performed [Col 9, lines 2-5 teach: In an outdoor scene, with significant veiling glare, the viewer can often just ignore the glare, but where it is stitched to another image that doesn't have the glare, the glare is very noticeable; and Col 9, lines 8-9 teach: In order to smoothly stitch images, the image processor can remove some of the veiling glare by applying an offset].].
Regarding claim 6: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein the pixel values of the first image and the second image are gradation values of R components, G components, and B components of the first image and the second image [Col; 9, line 21-28 teach: For the overlap region, the image processor calculates and stores a grid of subsampled average and variance statistics from both cameras after an alignment is done for the two images. Thus, the subsamples overlap from image to image and for a subsample, the average pixel value (this can be done on a color component by component basis) would be known for the same subsample of the scene for both cameras.], wherein the correction gain calculation unit calculates a ratio of a representative value among gradation values of pixels of the first comparative image taken from the first image, to a representative value among gradation values of pixels of the second comparative image taken from the second image, as the correction gain, for each of the R components, G components, and B components of the post-conversion second image, and wherein the correction unit corrects gradation values of pixels of the post-conversion second image, for each of the R components, G components, and B components of the post-conversion second image, based on respective correction gains calculated [Col 9, lines 59-65 teach: In one approach, the image processor accumulates pre-gamma RGB average statistics over multiple frames to build a persistent model of how the illuminant (approximated by white balance red and blue gains) causes uniformity differences between cameras and generates multipliers (step 806) for the input signal to use in addition to the offsets.].
Regarding claim 10: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein the representative value is a mean value Col 11, lines 8-10 teach: For each section, the image processor calculates a first average pixel intensity value for the first region and a second average pixel intensity value for the second region.]
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 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.
Claim(s) 3-5 and 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over ADCOCK in view of THOMAS et al, (From IDS: Cross-Media Color Reproduction and Display Characterization from Advanced Color Image Processing and Analysis, January 2013, page 97).
Regarding claim 3: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein, in the predetermined image conversion, a pixel value in the first image and a pixel value in the second image [Col 6, lines 31-36 teach: The image processor can consider the image values from the cameras is setting those values, such as by asking for test images, making measurements on those test images, sending commands to set camera parameters, and then obtaining the actual images that are to be used.]
However, ADCOCK does not explicitly teach subjected to a multiplication by 1/n (where n > 1) and then to an addition of m (where m > 0), and post-multiplication, post-addition pixel values serve as pixel values in the post-conversion first image and the post-conversion second image.
In a related field of endeavor, THOMAS teaches a multiplication by 1/n (where n > 1) and then to an addition of m (where m > 0), and post-multiplication, post-addition pixel values serve as pixel values in the post-conversion first image and the post-conversion second image [¶3 teaches: This model is called gain-offset-gamma (GOG)].
Given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate THOMAS’ teaching of predetermined image conversion into ADCOCK’S synthetic image generation system for the benefit, as taught by THOMAS, of a normalized digital input using a simple “gamma” model. [See THOMAS, ¶2-3]
Regarding claim 4: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein, in the predetermined image conversion, a pixel value in the first image and a pixel value in the second image [Col 6, lines 31-36 teach: The image processor can consider the image values from the cameras is setting those values, such as by asking for test images, making measurements on those test images, sending commands to set camera parameters, and then obtaining the actual images that are to be used.]
However, ADCOCK does not explicitly teach subjected to an addition of m (where m > 0), and post-addition values serve as pixel values in the post-conversion first image and the post-conversion second image.
In a related field of endeavor, THOMAS teaches a multiplication by 1/n (where n > 1) and then to an addition of m (where m > 0), and post-multiplication, post-addition pixel values serve as pixel values in the post-conversion first image and the post-conversion second image [¶3 teaches: This model is called gain-offset-gamma (GOG) with yh =1 and ah =1)].
The motivation to combine is the same as for claim 3. [See teaching above.]
Regarding claim 5: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein, in the predetermined image conversion, a pixel value in the first image and a pixel value in the second image [Col 6, lines 31-36 teach: The image processor can consider the image values from the cameras is setting those values, such as by asking for test images, making measurements on those test images, sending commands to set camera parameters, and then obtaining the actual images that are to be used.]
However, ADCOCK does not explicitly teach subjected to an addition of m (where m > 0), wherein, when a value that exceeds a maximum value that the pixel value in the first image and the pixel value in the second image can take is not produced among post-addition pixel values, the post-addition pixel values serve as pixel values in the post-conversion first image and the post-conversion second image, and wherein, when the value that exceeds the maximum value is produced among the post-addition pixel values, the pixel value in the first image and the pixel value in the second image are subjected to a multiplication by 1/n (where n > 1) and then to the addition of m, and post-multiplication, post-addition values serve as the pixel values in the post-conversion first image and the post-conversion second image.
In a related field of endeavor, THOMAS teaches subjected to an addition of m (where m > 0), wherein, when a value that exceeds a maximum value that the pixel value in the first image and the pixel value in the second image can take is not produced among post-addition pixel values, the post-addition pixel values serve as pixel values in the post-conversion first image and the post-conversion second image, and wherein, when the value that exceeds the maximum value is produced among the post-addition pixel values, the pixel value in the first image and the pixel value in the second image are subjected to a multiplication by 1/n (where n > 1) and then to the addition of m, and post-multiplication, post-addition values serve as the pixel values in the post-conversion first image and the post-conversion second image [¶3 teaches: This model is called gain-offset-gamma (GOG) where yh and ah values correspond with multiplication by a fraction)].
The motivation to combine is the same as for claim 3. [See teaching above.]
Regarding claim 8: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein the pixel values of the first image and the second image are gradation values of R components, G components, and B components of the first image and the second image, wherein the correction gain calculation unit calculates a ratio of a representative value among gradation values of pixels of the first comparative image taken from the first image, to a representative value among gradation values of pixels of the second comparative image taken from the second image, as the correction gain, for each of the R components, G components, and B components of the post-conversion second image, wherein the correction unit corrects gradation values of pixels of the post-conversion second image, for each of the R components, G components, and B components of the post-conversion second image, based on respective correction gains calculated [Col 9, lines 59-65 teach: In one approach, the image processor accumulates pre-gamma RGB average statistics over multiple frames to build a persistent model of how the illuminant (approximated by white balance red and blue gains) causes uniformity differences between cameras and generates multipliers (step 806) for the input signal to use in addition to the offsets.].
However, ADCOCK does not explicitly teach wherein the R components, G components, and B components of the first image and the second image are represented in 256 levels of gradation, and wherein the predetermined image conversion is performed such that a gradation value in the first image and a gradation value in the second image are subjected to a multiplication by 1/2 and then to an addition of 128, for each of the R components, G components, and B components of the first image and the second image, and post-multiplication, post-addition values serve as gradation values in the post-conversion first image and the post-conversion second image.
In a related field of endeavor, THOMAS teaches the R components, G components, and B components of the first image and the second image are represented in 256 levels of gradation, and wherein the predetermined image conversion is performed such that a gradation value in the first image and a gradation value in the second image are subjected to a multiplication by 1/2 and then to an addition of 128, for each of the R components, G components, and B components of the first image and the second image, and post-multiplication, post-addition values serve as gradation values in the post-conversion first image and the post-conversion second image [¶3 teaches: This model is called gain-offset-gamma (GOG) (i.e. where yh and ah values correspond with 256 levels of gradation)].
The motivation to combine is the same as for claim 3. [See teaching above.]
Regarding claim 9: the essence of the claim is taught above in the rejection of claim 1.
In addition, ADCOCK teaches wherein the pixel values of the first image and the second image are gradation values of R components, G components, and B components of the first image and the second image, wherein the correction gain calculation unit calculates a ratio of a representative value among gradation values of pixels of the first comparative image taken from the first image, to a representative value among gradation values of pixels of the second comparative image taken from the second image, as the correction gain, for each of the R components, G components, and B components of the post-conversion second image [Col 9, lines 59-65 teach: In one approach, the image processor accumulates pre-gamma RGB average statistics over multiple frames to build a persistent model of how the illuminant (approximated by white balance red and blue gains) causes uniformity differences between cameras and generates multipliers (step 806) for the input signal to use in addition to the offsets.].
However, ADCOCK does not explicitly teach wherein the correction unit corrects gradation values of pixels of the post-conversion second image, for each of the R components, G components, and B components of the post-conversion second image, based on respective correction gains calculated, wherein the R components, G components, and B components of the first image and the second image are represented in 256 levels of gradation, and wherein the predetermined image conversion is performed such that gradation values in a pre-conversion image is subjected to an addition of 128, for each of the R components, G components, and B components of the pre-conversion image, and post-addition values serve as lower gradation values in a post-conversion image with an increased number of levels of gradation.
In a related field of endeavor, THOMAS teaches wherein the correction unit corrects gradation values of pixels of the post-conversion second image, for each of the R components, G components, and B components of the post-conversion second image, based on respective correction gains calculated, wherein the R components, G components, and B components of the first image and the second image are represented in 256 levels of gradation, and wherein the predetermined image conversion is performed such that gradation values in a pre-conversion image is subjected to an addition of 128, for each of the R components, G components, and B components of the pre-conversion image, and post-addition values serve as lower gradation values in a post-conversion image with an increased number of levels of gradation [¶3 teaches: This model is called gain-offset-gamma (GOG) (i.e. where yh and ah values correspond with 256 levels of gradation)].
The motivation to combine is the same as for claim 3. [See teaching above.]
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over ADCOCK in view of HIRAI et al, (US 2014/0079333).
Regarding claim 7: the essence of the claim is taught above in the rejection of claim 1.
However, ADCOCK does not expressly teach wherein the pixel values of the first image and the second image are brightness values of the first image and the second image, wherein the correction gain calculation unit calculates a ratio of a representative value among brightness values of pixels of the first comparative image taken from the first image, to a representative value among brightness values of pixels of the second comparative image taken from the second image, as the correction gain, and wherein the correction unit corrects brightness values of pixels of the post-conversion second image based on the correction gain.
In a related field of endeavor, HIRAI teaches wherein the pixel values of the first image and the second image are brightness values of the first image and the second image, wherein the correction gain calculation unit calculates a ratio of a representative value among brightness values of pixels of the first comparative image taken from the first image, to a representative value among brightness values of pixels of the second comparative image taken from the second image, as the correction gain, and wherein the correction unit corrects brightness values of pixels of the post-conversion second image based on the correction gain [¶0064 teaches: According to the computation formulae above, a weight is appropriately determined and discontinuity in luminance is reduced.].
Given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate HIRAI’s teaching of a ratio of a representative value among brightness values into ADCOCK’S synthetic image generation system for the benefit, as taught by HIRAI, of reduce a subject blur by using the image information of the input image only. [See HIRAI, ¶0008]
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over ADCOCK in view of KATO et al, (US 2002/0196340).
Regarding claim 11: the essence of the claim is taught above in the rejection of claim 1.
However, ADCOCK does not expressly teach mounted in a car, the rear image display system comprising: a monitor configured to display the synthetic image generated by the synthetic image generation system; a first camera configured to capture an image showing a rear view from the car seen from a side part of the car; and a second camera configured to capture an image showing a rear view from the car seen from a rear part of the car.
In a related field of endeavor, KATO teaches: mounted in a car, the rear image display system comprising: a monitor configured to display the synthetic image generated by the synthetic image generation system [¶0002 teaches: image synthesis display method and apparatus for a vehicle camera for generating in real time a synthesized image that can easily be viewed on a display screen]; a first camera configured to capture an image showing a rear view from the car seen from a side part of the car [¶0005 teaches: cameras 2 and 4, mounted at the front and the rear on the vehicle's left side]; and a second camera configured to capture an image showing a rear view from the car seen from a rear part of the car [¶0005 teaches: cameras 3 and 5, mounted at the front and the rear on the vehicle's right side].
Given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate HIRAI’s teaching of a ratio of a representative value among brightness values into ADCOCK’S synthetic image generation system for the benefit, as taught by HIRAI, of reduce a subject blur by using the image information of the input image only. [See HIRAI, ¶0008]
Conclusion
Prior art not relied upon: Please refer to the references listed in an attached PTO-892 and that are not relied upon for the claim rejections detailed above. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
In particular, HOSONO et al., (US 2015/0206296) teaches an image acquiring section for acquiring first image data and second image data; a subtraction processing section for obtaining a difference value for each pixel for at least a part of the first image data and at least a part of the second image data; a filter processing section for applying filter processing based on a spatial frequency of an image to the difference value; and an image composition section for compositing at least a part of the first image data with at least a part of the second image data on the basis of an output of the filter processing;
HIRAI et al., (US 2014/0079333) teaches an image processing device that performs image processing on a composite image obtained by merging a first image and a second image having different exposure conditions;
KATO et al., (US 2002/0196340) teaches camera images synthesized to display a synthesized image on the screen of a display device wherein the pixel data for the camera images constituting the synthesized image are compensated for, so that differences in the pixel data for adjacent camera images is reduced; and
NAKAMURA et al., (US Patent No 6,215,914) teaches a picture processing apparatus which can reduce matching errors and shorten a processing time for matching; and
In the case of amending the claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
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/MARNIE A MATT/ Primary Examiner, Art Unit 2485