Differentiation of illumination and reflection boundaries
The present invention provides methods and apparatus for image processing in which brightness boundaries of an image are identified and analyzed in at least two, and more preferably three or more, spectral bands to distinguish illumination boundaries from reflectance boundaries. For example, in one embodiment of the invention, a brightness boundary of the image can be identified as an illumination boundary if at least two wavelength bands of the image exhibit a substantially common shift in brightness across the boundary.
1 . A method of differentiating an illumination boundary from a reflectance boundary in an image, comprising:
identifying a brightness boundary in the image, and
identifying the boundary as an illumination boundary if at least two wavelength bands of said image exhibit a substantially common shift in brightness across said boundary.
2 . The method of claim 1 , further comprising identifying the brightness boundary as a reflectance boundary if at least two wavelength bands of said image exhibit an increase and a decrease, respectively, in brightness from one side of said boundary to another.
3 . The method of claim 1 , further comprising identifying said brightness boundary as a concurrent brightness and reflectance boundary if at least two wavelength bands of the image exhibit a decrease in brightness from one side of the boundary to another such that the degree of decrease of one band is substantially different than that of the other band.
4 . The method of claim 1 , wherein said substantially common shift comprises a decrease in brightness of one wavelength band that differs from a corresponding decrease in brightness of at least another wavelength band by less than a few percent.]
5 . A method for distinguishing reflectance boundaries from illumination boundaries in an image, comprising
identifying one or more brightness boundaries in the image,
for each of said boundaries, determining brightness values of two or more wavelength bands on either side of the boundary, and
identifying a boundary as a reflectance or an illumination boundary based on a comparison of a change in said brightness values across that boundary for each of said wavelength bands relative to a corresponding change in the other wavelength bands.
6 . The method of claim 5 , further comprising identifying a boundary as an illumination boundary when said two or more wavelength bands exhibit a decrease in brightness from one side of the boundary to the other.
7 . The method of claim 5 , further comprising identifying a boundary as a reflectance boundary when at least one of said wavelength bands exhibits a decrease in brightness from one side of the boundary to the other and at least one of the other wavelength bands exhibits an increase in brightness from said one side of the boundary to the other.
8 . The method of claim 5 , wherein the step of identifying brightness boundaries applying an edge detection technique to the image.
9 . The method of claim 5 , wherein the image is an image of a naturally illuminated scene.
10 . The method of claim 5 , wherein said wavelength bands include long, medium, and short wavelength bands, respectively.
11 . The method of claim 5 , wherein at least two of said wavelength bands are partially overlapping.
12 . A method of distinguishing reflectance boundaries from illumination boundaries in an image of a scene, comprising
identifying one or more brightness boundaries in the image, and
identifying each brightness boundary as a reflection or an illumination boundary based on a comparison of a spectral signature related to brightness values associated with at least two wavelength bands of the image on one side of the boundary with a corresponding spectral signature on the other side of the boundary.
13 . The method of claim 12 , wherein said spectral signature is characterized by a difference in brightness values associated with said at least two wavelength bands.
14 . The method of claim 13 , further comprising identifying a brightness boundary as an illumination boundary when said spectral signatures on two sides of the boundary are both positive or both negative.
15 . The method of claim 13 , further comprising identifying a brightness boundary as a reflectance boundary when said spectral signatures on two sides of the boundary exhibit different signs.
16 . A method of identifying a brightness boundary in an image as either an illumination boundary or a reflectance boundary, comprising
identifying a brightness boundary in the image,
determining brightness values in at least two wavelength bands on either side of the boundary, and
identifying the boundary as a reflectance or an illumination boundary based on correlation of changes of brightness values across the boundary in said wavelength bands.
17 . The method of claim 16 , further comprising identifying a brightness boundary as a reflectance boundary when at least one of the wavelength bands exhibits a decrease, and the other wavelength band exhibits an increase, in brightness values from a bright side of the boundary to the other.
18 . The method of claim 17 , further comprising identifying a brightness boundary as an illumination boundary when said wavelength bands exhibit a decrease in brightness values from a bright side of the boundary to the other.
19 . A method of distinguishing illumination boundaries from reflectance boundaries in an image of a scene, comprising:
identifying a plurality of brightness boundaries in the image, each brightness boundary separating a high brightness side from a low brightness side,
for each of three selected wavelength bands of the image and each of the brightness boundaries, determining image brightness on each side of the boundary,
for each of said wavelength bands and each of the brightness boundaries, determining a brightness difference across the boundary,
for each of said brightness boundaries, generating a three-component vector wherein each component is formed as a ratio of an absolute value of brightness difference across the boundary relative to brightness on the bright side of the boundary corresponding to one of the wavelength bands,
normalizing said vectors,
identifying a boundary as an illumination boundary if a normalized vector corresponding to said boundary forms a cluster with one or more vectors corresponding to other boundaries.
20 . The method of claim 19 , further characterizing each of said three-component vectors ({overscore (V)}) as follows:
V
_
=
(
D
L
B
L
'
,
D
M
B
M
'
,
D
S
B
S
'
)
wherein L, M, and S denote said three wavelength bands, D L , D M , and D S denote brightness values in the low brightness side of the boundary for each of the three wavelength bands, respectively, and B′ L , B′ M , B′ S are defined, respectively, as
B′ L =B L −D L ; B′ M =B M −D M ; B′ S =B S −D S ,
wherein B L , B M , and B S are brightness values in the high brightness of the boundary for each of the wavelength bands, respectively.
21 . The method of claim 20 , further comprising normalizing said vector {overscore (V)} to obtain a normalized vector ({overscore (V)} N ) defined as follows:
V
_
N
=
V
_
V
,
wherein ∥V∥ denotes the norm of {overscore (V)}.
22 . The method of claim 20 , wherein said wavelength bands include long, medium, and short wavelength bands, respectively.
23 . An imaging system, comprising
an image-capture device for generating a multi-spectral image of a scene, and
an image processing module operating on image to identify one or more brightness boundaries therein, and to differentiate said brightness boundaries into illumination and reflectance boundaries.
24 . The imaging system of claim 23 , wherein said image processing module comprises a storage for storing an image data received from the image-capture device.
25 . The imaging system of claim 24 , wherein said image processing module comprises a processor programmed to operate on said image data to identify said brightness boundaries and to classify them into illumination and reflectance boundaries.
26 . The imaging system of claim 2531 , wherein said processor comprises a module for operating on said image to determine brightness boundaries therein.
27 . The imaging system of claim 26 , wherein said processor further comprises another module for utilizing information regarding said brightness boundaries and said image data to classify said boundaries into illumination and reflectance boundaries.