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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1 June, 2026 has been entered.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on 19 November, 2025.
Response to Amendment
The amendment filed 13 May, 2026 has been entered.
The amendment of claims 1, 3 – 6, 10, and 12 – 14 has been acknowledged.
Response to Arguments
Applicant’s arguments, see page 11, section “Claim Rejection under 35 U.S.C. § 112”, filed 8 May, 2026 with respect to the rejection of claims 1, and 10 have been fully considered and are persuasive. The rejection of claims 1 and 10 under 35 U.S.C. § 112(b) has been withdrawn.
Applicant’s arguments, see page 11, section “Claim Rejection under 35 U.S.C. §§ 102 and 103”, filed 26 January, 2026 with respect to the rejection of claims 1, 2, 10, 11, and 19 have been fully considered and are persuasive. The rejection of claims 1, 2, 10, 11, and 19 have been withdrawn. However, upon further examination, a new rejection has been made under 35 U.S.C. § 102.
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.
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.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitations are: a “dark channel image determination unit configured to”, an “atmospheric luminosity determination unit configured to”, and a “dehazing processing unit configured to” in claims 10, 11, 12, 13, 15, 16, 17, and 18.
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
The following is a quotation of the appropriate paragraphs of pre-AIA 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) the invention was known or used by others in this country, or patented or described in a printed publication in this or a foreign country, before the invention thereof by the applicant for a patent.
(b) the invention was patented or described in a printed publication in this or a foreign country or in public use or on sale in this country, more than one year prior to the date of application for patent in the United States.
Claims 1, 2, 10, and 11 are rejected under pre-AIA 35 U.S.C. 102(a)(1) as being anticipated by He et al (Kaiming He, Jian Sun and Xiaoou Tang, "Single image haze removal using dark channel prior," 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 2009, pp. 1956-1963, doi: 10.1109/CVPR.2009.5206515.) in view of Hirayama et al (U.S. Patent Publication No. 2018/0160039 A1, hereinafter “Hirayama”).
Regarding claim 1, He teaches an image processing method, comprising:
determining a dark channel image of an input image (Equation 5; Page 1957, Section “Dark Channel Prior”: The dark channel prior is based on the following observation on haze-free outdoor images: in most of the non-sky patches, at least one color channel has very low intensity at some pixels.);
determining an atmospheric luminosity according to a grayscale histogram of the dark channel image based on a first point of the grayscale histogram in response to the input image not including a sky area or a second point of the grayscale histogram in response to the input image including the sky area (Figure 4; Figure 6(a); Figure 7, including images that both comprise sky and non-sky areas; Page 1960, Section “Estimating the Atmospheric Light”: We can use the dark channel to improve the atmospheric light estimation. We first pick the top 0.1% brightest pixels in the dark channel. These pixels are in the red rectangle in Figure 6(a).; Examiner’s note: The limitation “based on a first point… in the response to the input image not including the sky area” under broadest reasonable interpretation can be read as any point of any dark channel image that does not comprise sky and as such, selecting the top 0.1% of the brightest pixels in the dark channel is understood to read on the selecting of a point. Additionally, the points selected in figure 6(a) are of area that does not comprise sky.), the first point corresponding to a number of pixels above a threshold, and the second point corresponding to a valley in the grayscale histogram (Page 1960, Section “Estimating the Atmospheric Light”: These pixels are most haze-opaque (bounded by yellow lines in Figure 6(b)). Among these pixels, the pixels with highest intensity in the input image I is selected as the atmospheric light.; Examiner’s note: The pixels selected in 6(a) are the most opaque but are not pixels of a sky area. As such, the pixels chosen are of a first point which are values above an opaqueness threshold. The art’s description of “pixels with the highest intensity” implies a threshold wherein the pixels selected are the most intense, top 0.1%, excluding all pixels below 99.9%.); and
determining a dehazing image of the input image based on the atmospheric luminosity (Equation 16; Page 1960, Section “Recovering the Scene Radiance”: The final scene radiance J(x) is recovered by:
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Regarding claim 2, He teaches the image processing method according to claim 1.
Additionally, He teaches wherein the determining the atmospheric luminosity according to the grayscale histogram of the dark channel image comprises:
obtaining the grayscale histogram of the dark channel image based on counting pixels of the dark channel image (Figure 4(a) – 4(c); Page 1958, Col. 2, ¶ 1: Figure 4(a) is the intensity histogram over all 5,000 dark channels and Figure 4(b) is the corresponding cumulative histogram.); and
determining the atmospheric luminosity by performing a grayscale traversal on the grayscale histogram (Page 1960, Section “Estimating the Atmospheric Light”: We can use the dark channel to improve the atmospheric light estimation. We first pick the top 0.1% brightest pixels in the dark channel. These pixels are in the red rectangle in Figure 6(a).; Page 1958, Col. 2, ¶ 1: We also compute the average intensity of each dark channel and plot the corresponding histogram in Figure 4(c).; Examiner’s note: Selecting the top 0.1% brightest pixels from an image is understood to read on “traversal on the grey histogram” as a histogram is an ordering of values of pixels. Under broadest reasonable interpretation, any process which determines the brightness values of pixels and selects from a criteria is understood by be a traversal of these values.).
The rejection of method claim 1 above applies mutatis mutandis to the corresponding limitations of device claim 10 while noting that the rejection above cites to both device and method disclosures.
For the image processing device, dark channel image determination unit, atmospheric luminosity determination unit, and dehazing processing unit, see He (page 1961, Section “Experimental Results”: The patch size is set to 15 × 15 for a 600 × 400 image. In the soft matting, we use Preconditioned Conjugate Gradient (PCG) algorithm as our solver. It takes about 10-20 seconds to process a 600×400 pixel image on a PC with a 3.0 GHz Intel Pentium 4 Processor).
The rejection of method claim 2 above applies mutatis mutandis to the corresponding limitations of device claim 11 while noting that the rejection above cites to both device and method disclosures.
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 19 are rejected under 35 U.S.C. 103 as being unpatentable over He et al (Kaiming He, Jian Sun and Xiaoou Tang, "Single image haze removal using dark channel prior," 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 2009, pp. 1956-1963, doi: 10.1109/CVPR.2009.5206515.) in view of Li et al (U.S. Patent Publication No. 2018/0122051 A1, hereinafter “Li”)
Regarding claim 19, the He teaches an electronic apparatus, comprising:
at least one processor (¶ 0106: A “circuit” may be understood as any kind of a logic implementing entity, which may be special purpose circuitry or a processor executing software stored in a memory, firmware, or any combination thereof.);
at least one non-volatile memory configured to store computer executable instructions, wherein the computer executable instructions, based on being executed by the at least one processor (¶ 0109: According to various embodiments, a non-transitory computer readable medium with a program stored thereon for processing an input image to generate a de-hazed image is provided.), cause the at least one processor to perform the image processing method according to claim 1.
Li is considered to be analogous art as it pertains to haze removal from images. Therefore, it would have been obvious to one of ordinary skill in the art to combine the system for single image haze removal (as taught by He) and the method for image haze removal (as taught by Li) before the effective filing date of the claimed invention. The motivation for this combination of references would be Li utilizes a compensation term that is adaptive to the haze degree of the input image. This term is automatically detected by using the histogram of the input image and reduces halo artifacts and limits amplification noise in the bright regions of the input image. (See ¶ 0075).
This motivation for the combination of He and Li is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Allowable Subject Matter
Claims 6 - 9 are allowed.
The following is a statement of reasons for the indication of allowable subject matter:
The closest prior art over He et al (Kaiming He, Jian Sun and Xiaoou Tang, "Single image haze removal using dark channel prior," 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 2009, pp. 1956-1963, doi: 10.1109/CVPR.2009.5206515.) in view of Hirayama et al (U.S. Patent Publication No. 2018/0160039 A1, hereinafter “Hirayama”) in view of secondary art Li et al (U.S. Patent Publication No. 2018/0122051 A1, hereinafter “Li”) teaches that it was known at the time the application was filed to perform an image processing method comprising, determining a dark channel image of an input image determining an atmospheric luminosity according to a grayscale histogram of the dark channel image and determining a dehazing image of the input image based on the atmospheric luminosity, and wherein the determining the dehazing image of the input image based on the atmospheric luminosity comprises determining a transmissivity based on a luma image of the input image and the atmospheric luminosity.
However, the prior art, alone or in combination, does not appear to teach or suggest determining a transmissivity mapping weight based on the transmissivity, determining a dehazing luma image based on the luma image, the atmospheric luminosity, and the transmissivity mapping weight, and determining the dehazing image based at least on a chroma image of the input image and the dehazing luma image.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Claims 3 – 5, and 12 - 18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hong et al (U.S. Patent Publication No. 2023/0306569 A1) teaches steps of processing an antibright channel image according to a defogging model to obtain a dark area enhanced image including determining an anti-bright channel adjustment parameter and an anti-bright channel atmospheric light intensity parameter and performing defogging model calculation according to the original image, the anti-bright channel adjustment parameter, the anti-bright channel atmospheric light intensity parameter and the anti-bright channel image to obtain the dark area enhanced image.
Sekine et al (U.S. Patent Publication No. 2024/0249398 A1) teaches an image processing apparatus that calculates an atmospheric transmittance distribution based on an input image and, based on an illumination distribution that has been calculated based on that transmittance distribution, sharpens that input image.
Huang et al (U.S. Patent No. 9177363 B1) teaches a method for restoring image visibility where a transmission map for each pixel is determined, then the transmission map is refined according to edge information. The refined transmission map is gamma corrected and then used to recover scene radiance using the gamma corrected refined transmission map, a color difference value, and the atmospheric light.
Yang et al (W. Yang, Z. Xiao, Q. Wang and X. Liu, "A Method for Improving the Definition of Scene in Fog Image," 2009 International Conference on Computational Intelligence and Software Engineering, Wuhan, China, 2009, pp. 1-4, doi: 10.1109/CISE.2009.5362842.) teaches a method of hazy image correction using sky region detection and histogram equalization within an image.
Conclusion
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/ANDREW B. JONES/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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