{"search_session":{},"preferences":{"l":"en","queryLanguage":"en"},"patentId":"199-342-841-252-649","frontPageModel":{"patentViewModel":{"ref":{"entityRefId":"199-342-841-252-649","entityRefType":"PATENT"},"entityMetadata":{"linkedIds":{"empty":true},"tags":[],"collections":[{"id":10791,"type":"PATENT","title":"The Hebrew University of Jerusalem - Patent Portfolio","description":"","access":"OPEN_ACCESS","displayAvatar":true,"attested":false,"itemCount":7593,"tags":[],"user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"notes":[{"id":8259,"type":"COLLECTION","user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"text":"
Search Applicants and Owners separately: \"hebrew univ* jerusalem\"; \"hebrew univ* jerus*\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 1457
Search Applicants and Owners separately: \"hebrew univ* jerusalem\"; \"hebrew univ* jerus*\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 1457
modeling a surface radiance vector J of the input image I as a product of a surface albedo coefficient R and a shading factor l;\n
determining, by a processor for each of the plurality of pixels, a value of a transmission t of the pixel, such that a covariance CΩ between the transmission t and the shading factor l is minimized; and\n
recovering, by the processor, the surface radiance vector J based at least in part on the determined value of the transmission t for each pixel."],"number":1,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 1 further comprising:\n
breaking the surface albedo coefficient R into a sum of two components, a first component parallel to an airlight color vector A and a second component comprising a residual vector R′, wherein the residual vector R′ comprises an amount of airlight expressed by an unknown scalar value η;\n
projecting the input image I onto the airlight color vector A to create an airlight projection IA; and\n
projecting the input image I along the residual vector R′ to create a residual projection IR′."],"number":2,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 2, wherein determining, for each of the plurality of pixels, a value of the transmission t further comprises:\n
selecting, for each of the plurality of pixels, a value for η, such that the covariance CΩ between the transmission t and the shading factor l is minimized, wherein η is based at least in part on the airlight projection IA and the residual projection IR′; and\n
determining, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η."],"number":3,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 3, wherein the covariance CΩ is defined as follows for any two functions ƒ and g\nCx(f,g)=1Wx∑y∈Ωx(f(y)-Ex(f))(g(y)-Ex(g))w(x,y),\nand\nEx(f)=1Wx∑y∈Ωxf(y)w(x,y),\nwherein x represents a pixel at location (x,y), Wx represents a normalizing weight given by Wx=ΣyεΩX w(x,y), Ωx represents a window of pixels centered around x, Ex represents a mean of ƒ in a window around x for every function ƒ, and w(x,y) represents a weighting function given by exp(−d(θ(x), θ(y))2/σθ2), wherein d represents a distance function, θ represents a measure of chromaticity, and σθ2 is a scale parameter."],"number":4,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 2, wherein the airlight projection IA is defined by IA(x)=I(x),A/∥A∥=t(x)l′(x)η+(1−t(x))∥A∥, wherein l′ represents a scaled shading factor."],"number":5,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 2, wherein the residual projection IR′ is defined by IR′(x)=√{square root over (∥I(x)∥2−IA(x)2)}{square root over (∥I(x)∥2−IA(x)2)}t(x)l′(x), wherein l′ represents a scaled shading factor."],"number":6,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 3, wherein determining, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η further comprises:\n
computing, for each of the plurality of pixels, an estimate of the transmission {circumflex over (t)}based at least in part on the selected value for η;\n
computing, for each of the plurality of pixels, a noise variance σt in {circumflex over (t)}; and\n
computing, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt."],"number":7,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 7, wherein computing, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt further comprises computing the transmission t using a Gauss-Markov random field model."],"number":8,"annotation":false,"claim":true,"title":false},{"lines":["The method of claim 7, wherein computing, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt further comprises:\n
comparing the noise variance σt of each pixel to a threshold;\n
discarding one or more pixels of the plurality of pixels based at least in part on the comparison; and\n
computing the transmission t for each remaining pixel."],"number":9,"annotation":false,"claim":true,"title":false},{"lines":["A method comprising:\n
receiving, from an image capture device, a single input image I comprising a plurality of pixels;\n
modeling a surface radiance vector J of the input image I as a product of a surface albedo coefficient R and a shading factor l;\n
breaking the surface albedo coefficient R into a sum of two components, a first component parallel to an airlight color vector A and a second component comprising a residual vector R′, wherein the residual vector R′ comprises an amount of airlight expressed by an unknown scalar value η;\n
projecting the input image I onto the airlight color vector A to create an airlight projection IA;\n
projecting the input image I along the residual vector R′ to create a residual projection IR′;\n
selecting, by a processor for each of the plurality of pixels, a value for η, such that a covariance CΩ between a transmission t of the pixel and the shading factor l is minimized, wherein η is based at least in part on the airlight projection IA and the residual projection IR′;\n
determining, by the processor for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η; and\n
recovering, by the processor, the surface radiance vector J based at least in part on the determined value of the transmission t for each pixel."],"number":10,"annotation":false,"claim":true,"title":false},{"lines":["An apparatus comprising:\n
a processor configured to:\n"],"number":11,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 11, wherein the processor is further configured to:\nreceive, from an image capture device, a single input image I comprising a plurality of pixels;\nmodel a surface radiance vector J of the input image I as a product of a surface albedo coefficient R and a shading factor l;\ndetermine, for each of the plurality of pixels, a value of a transmission t of the pixel, such that a covariance CΩ between the transmission t and the shading factor l is minimized; and\nrecover the surface radiance vector J based at least in part on the determined value of the transmission t for each pixel.\n
break the surface albedo coefficient R into a sum of two components, a first component parallel to an airlight color vector A and a second component comprising a residual vector R′, wherein the residual vector R′ comprises an amount of airlight expressed by an unknown scalar value η;\n
project the input image I onto the airlight color vector A to create an airlight projection IA; and\n
project the input image I along the residual vector R′ to create a residual projection IR′."],"number":12,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 12, wherein in order to determine, for each of the plurality of pixels, a value of the transmission t, the processor is further configured to:\n
select, for each of the plurality of pixels, a value for η, such that the covariance CΩ between the transmission t and the shading factor l is minimized, wherein η is based at least in part on the airlight projection IA and the residual projection IR′; and\n
determine, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η."],"number":13,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 13, wherein the covariance CΩ is defined as follows for any two functions ƒ and g\nCx(f,g)=1Wx∑y∈Ωx(f(y)-Ex(f))(g(y)-Ex(g))w(x,y),\nand\nEx(f)=1Wx∑y∈Ωxf(y)w(x,y),\nwherein x represents a pixel at location (x,y), Wx represents a normalizing weight given by Wx=ΣyεΩx w(x,y), Ωx represents a window of pixels centered around x, Ex represents a mean of ƒ in a window around x for every function ƒ, and w(x,y) represents a weighting function given by exp(−d(θ(x),θ(y))2/σθ2), wherein d represents a distance function, θ represents a measure of chromaticity, and σθ2 is a scale parameter."],"number":14,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 12, wherein the airlight projection IA is defined by IA(x)=I(x),A/∥A∥=t(x)l′(x)η+(1−t(x))∥A∥, by wherein l′ represents a scaled shading factor."],"number":15,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 12, wherein the residual projection IR′ is defined by IR′(x)=√{square root over (∥I(x)∥2−IA(x)2)}{square root over (∥I(x)∥2−IA(x)2)}=t(x)l′(x), wherein l′ represents a scaled shading factor."],"number":16,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 13, wherein in order to determine, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η, the processor is further configured to:\n
compute, for each of the plurality of pixels, an estimate of the transmission {circumflex over (t)} based at least in part on the selected value for η;\n
compute, for each of the plurality of pixels, a noise variance σt in {circumflex over (t)}; and\n
compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt."],"number":17,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 17, wherein in order to compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt, the processor is further configured to compute the transmission t using a Gauss-Markov random field model."],"number":18,"annotation":false,"claim":true,"title":false},{"lines":["The apparatus of claim 17, wherein in order to compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt, the processor is further configured to:\n
compare the noise variance σt of each pixel to a threshold;\n
discard one or more pixels of the plurality of pixels based at least in part on the comparison; and\n
compute the transmission t for each remaining pixel."],"number":19,"annotation":false,"claim":true,"title":false},{"lines":["A computer program product comprising a computer-readable storage medium having computer-readable program code portions stored therein, said computer-readable program code portions comprising:\n
a first executable portion for receiving, from an image capture device, a single input image I comprising a plurality of pixels;\n
a second executable portion for modeling a surface radiance vector J of the input image I as a product of a surface albedo coefficient R and a shading factor l;\n
a third executable portion for determining, for each of the plurality of pixels, a value of a transmission t of the pixel, such that a covariance CΩ between the transmission t and the shading factor l is minimized; and\n
a fourth executable portion for recovering the surface radiance vector J based at least in part on the determined value of the transmission t for each pixel."],"number":20,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 20, wherein the computer-readable program code portions further comprise:\n
a fifth executable portion for breaking the surface albedo coefficient R into a sum of two components, a first component parallel to an airlight color vector A and a second component comprising a residual vector R′, wherein the residual vector R′ comprises an amount of airlight expressed by an unknown scalar value η;\n
a sixth executable portion for projecting the input image I onto the airlight color vector A to create an airlight projection IA; and\n
a seventh executable portion for projecting the input image I along the residual vector R′ to create a residual projection IR′."],"number":21,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 21, wherein the third executable portion is further configured to:\n
select, for each of the plurality of pixels, a value for η, such that the covariance CΩ between the transmission t and the shading factor l is minimized, wherein η is based at least in part on the airlight projection IA and the residual projection IR′; and\n
determine, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η."],"number":22,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 22, wherein the covariance CΩ is defined as follows for any two functions ƒ and g\nCx(f,g)=1Wx∑y∈Ωx(f(y)-Ex(f))(g(y)-Ex(g))w(x,y),\nand\nEx(f)=1Wx∑y∈Ωxf(y)w(x,y),\nwherein x represents a pixel at location (x,y), Wx represents a normalizing weight given by Wx=ΣyεΩx w(x,y), Ωx represents a window of pixels centered around x, Ex represents a mean of ƒ in a window around x for every function ƒ, and w(x,y) represents a weighting function given by exp(−d(θ(x),θ(y))2/σθ2), wherein d represents a distance function, θ represents a measure of chromaticity, and σθ2 is a scale parameter."],"number":23,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 21, wherein the airlight projection IA is defined by IA(x)=I(x),A/∥A∥=t(x)l′(x)η+(1−t(x))∥A∥, wherein l′ represents a scaled shading factor."],"number":24,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 21, wherein the residual projection IR′ is defined by IR′(x)=√{square root over (∥I(x)∥2−IA(x)2)}{square root over (∥I(x)∥2−IA(x)2)}=t(x)l′(x), wherein l′ represents a scaled shading factor."],"number":25,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 22, wherein in order to determine, for each of the plurality of pixels, a value of the transmission t based at least in part on the selected value for η, the third executable portion is further configured to:\n
compute, for each of the plurality of pixels, an estimate of the transmission {circumflex over (t)} based at least in part on the selected value for η;\n
compute, for each of the plurality of pixels, a noise variance σt in {circumflex over (t)}; and\n
compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt."],"number":26,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 26, wherein in order to compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt, the third executable portion is further configured to compute the transmission t using a Gauss-Markov random field model."],"number":27,"annotation":false,"claim":true,"title":false},{"lines":["The computer program product of claim 26, wherein in order to compute, for each of the plurality of pixels, the transmission t based at least in part on the noise variance σt, the third executable portion is further configured to:\n
compare the noise variance σt of each pixel to a threshold;\n
discard one or more pixels of the plurality of pixels based at least in part on the comparison; and\n
compute the transmission t for each remaining pixel."],"number":28,"annotation":false,"claim":true,"title":false}]}},"filters":{"npl":[],"notNpl":[],"applicant":[],"notApplicant":[],"inventor":[],"notInventor":[],"owner":[],"notOwner":[],"tags":[],"dates":[],"types":[],"notTypes":[],"j":[],"notJ":[],"fj":[],"notFj":[],"classIpcr":[],"notClassIpcr":[],"classNat":[],"notClassNat":[],"classCpc":[],"notClassCpc":[],"so":[],"notSo":[],"sat":[]},"sequenceFilters":{"s":"SEQIDNO","d":"ASCENDING","p":0,"n":10,"sp":[],"si":[],"len":[],"t":[],"loc":[]}}