1. An \u03b1+\u03b2 titanium alloy sheet excellent in cold rollability and cold handling property, wherein:
(a) the normal direction of a hot-rolled sheet is taken as ND, the hot rolling direction is taken as RD, the hot-rolling width direction is taken as TD, the normal direction of the \u03b1-phase (0001) plane is taken as c-axis orientation, the angle formed between the c-axis orientation and the ND is taken as \u03b8, and the angle formed between a plane including the c-axis orientation and the ND, and a plane including the ND and the TD is taken as \u03c6;
(b1) among (0002) relative reflection intensities of X-ray by a crystal grain where \u03b8 is 0\xb0 or more and 30\xb0 or less, and \u03c6 falls in the entire circumference (\u2212180 to 180\xb0), the maximum intensity is taken as XND;
(b2) among (0002) relative reflection intensities of X-ray caused by a crystal grain where \u03b8 is 80\xb0 or more and less than 100\xb0, and \u03c6 falls in \xb110\xb0, the maximum intensity is taken as XTD; and
(c) XTDXND is 5.0 or more.
2. The \u03b1+\u03b2 titanium alloy sheet excellent in cold rollability and cold handling property according to claim 1, wherein the \u03b1+\u03b2 titanium alloy sheet comprises, in mass %, Fe: 0.8 to 1.5% and N: 0.020% or less, and contains O, N and Fe to satisfy the condition that Q (%) defined by the following formula (1) is 0.34 to 0.55, with the balance being Ti and unavoidable impurities:
Q (%)=O+2.77.N+0.1.Fe\u2003\u2003(1)
wherein O: the content (mass %) of O,
N: the content (mass %) of N, and
Fe: the content (mass %) of Fe.
3. A process for producing an 11+13 titanium alloy sheet excellent in cold rollability and cold handling property according to claim 1, wherein:
at the time of hot-rolling an \u03b1+\u03b2 titanium alloy, the titanium alloy before hot rolling is heated to a temperature ranging of (\u03b2 transformation temperature +20\xb0 C.) or more and (\u03b2 transformation point +150\xb0 C.) or less, and is hot-rolled uni-directionally by setting the hot rolling finishing temperature to be (\u03b2 transformation temperature \u2212200\xb0 C.) or more and (\u03b2 transformation temperature \u221250\xb0 C.) or less, such that the sheet thickness reduction ratio defined by the following formula becomes 90% or more:
Sheet thickness reduction ratio (%)={(sheet thickness before cold rolling\u2212sheet thickness after cold rolling)(sheet thickness before cold rolling)}\xb7100.
4. A process for producing an \u03b1+\u03b2 titanium alloy sheet excellent in cold rollability and cold handling property according to claim 2, wherein:
at the time of hot-rolling an \u03b1+\u03b2 titanium alloy, the titanium alloy before hot rolling is heated to a temperature ranging of (\u03b2 transformation temperature +20\xb0 C.) or more and (\u03b2 transformation point +150\xb0 C.) or less, and is hot-rolled uni-directionally by setting the hot rolling finishing temperature to be (\u03b2 transformation temperature \u2212200\xb0 C.) or more and (\u03b2 transformation temperature \u221250\xb0 C.) or less, such that the sheet thickness reduction ratio defined by the following formula becomes 90% or more:
Sheet thickness reduction ratio (%)={(sheet thickness before cold rolling\u2212sheet thickness after cold rolling)(sheet thickness before cold rolling)}\xb7100.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An image color correction method, wherein a corrected image is computed from original color components in an input image, the method comprising the steps of
computing color components of the corrected image corresponding to an interpolation between a first and second corrected color components vectors, wherein
the first corrected color component vector corresponds at least partly to scaling all color components of original color component vectors from the input image by factors that reduce a deviation of a characteristic color component vector for the input image from a target vector, and wherein
the second corrected color component vector corresponds to at least partial replacement of at least one of the color components of the original color component vectors from the input image by values computed from the other color components of the original color component vectors the input image;
computing an interpolation coefficient from a ratio of an average value of the at least one of the color components of the original color component vectors of the input image or one or more reference images and an average obtained from one or more of the other color components of the original color component vectors from the input image or the one or more reference images;
controlling a position of the interpolation between the first and second corrected color component vectors by said interpolation coefficient, the position being moved increasingly toward the second corrected color component vector with decreasing values of said ratio.
2. An image color correction method according to claim 1, wherein the corrected image correspond to an interpolation between the original color component vector from the input image, a first result of a color transformation comprising scaling all color components and a second result of a color space projection comprising replacement of at least one of the color components of the original color component vectors from the input image by values computed from the other color components of the original color component vectors from the input image.
3. An image color correction method according to claim 1, wherein the first corrected color component vector corresponds to a result of a one to one color transformation wherein the color components are multiplied by scale factors that map the characteristic color component vector to a grey vector, or to a mapped color vector between the characteristic color vector and the grey vector.
4. An image color correction method according to claim 1, wherein color components of the characteristic color component vector are averages of color components of the original color component vectors from the input image.
5. An image color correction method according to claim 1, wherein the second corrected color component vector corresponds to a result of a projection wherein the color components are mapped dependent on the one or more of the other color components, or to a mapped color vector between the characteristic color vector and the result of the color projection.
6. An image color correction method according to claim 1, wherein the at least one of the color components is the blue color component.
7. An image color correction method according claim 1, wherein the at least one of the color components is computed by applying respective factors determined from the characteristic color vector to a sum of the other color components in the input image and to the at least one of the color components from the input image respectively, and the other color components are computed by applying one or more further respective factors to one or more of the other color components from the input image respectively.
8. An image color correction method according to claim 1, wherein the first and second corrected color component vector are computed from the color components of the input image, and the corrected image is computed by interpolating between the first and second corrected color component vector.
9. An image processing system configured to compute a corrected image from original color components in an input image, the system comprising
a module for computing an interpolation coefficient from a ratio of an average value of the at least one of the color components of original color component vectors from the input image or one or more reference images and an average obtained from one or more of the other color component values of the original color component vectors from the input image or the or one or more reference images;
a module for computing color component vectors of the corrected image corresponding to an interpolation between a first and second corrected color component vectors, the module for computing color component vectors of the corrected image controlling a position of the interpolation between the first and second corrected color component vectors by said interpolation coefficient, the position being moved increasingly toward the second corrected color component vectors with decreasing values of said ratio, wherein
the first corrected color component vector corresponds at least partly to scaling all color components from the input image by factors that reduce a deviation of a characteristic color component vector for the input image from a target color component vector, and wherein
the second corrected color component vector corresponds to at least partial replacement of at least one of the color components of the original color component vector from the input image by values computed from the other color components of the original color component vector from the input image.
10. An image processing system according to claim 9, wherein the first corrected color component vector corresponds to a result of a one to one color transformation wherein the color components are multiplied by scale factors that map the characteristic color component vector to a grey vector, or to a mapped color component vector between the characteristic color component vector and the grey vector.
11. An image processing system according to claim 9, wherein color components of the characteristic color vector are averages of color components in the input image.
12. An image processing system according to claim 9, wherein the second corrected color component vector corresponds to a result of a color projection, wherein the color components are mapped dependent on the one or more of the other color components, or to a mapped color vector between the characteristic color vector and the result of the many to one color mapping.
13. An image processing system according to claim 9, wherein the at least one of the color components is the blue color component.
14. (canceled)
15. A tangible computer readable medium, comprising instructions for a programmable computer that, when executed by the programmable computer, causes the programmable computer to execute the method of claim 1.
16. An image color correction method according to claim 1, comprising contrast enhancement by amplifying deviations of image intensity from an averaged image intensity, using an averaged image intensity derived from the average values used for computing an interpolation coefficient.
17. An image color correction method according to claim 16, wherein the average values are local average values, computed by means of weighted averaging using image gradient dependent weighting coefficients.