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MatExpr Class Reference
[Basic structures]
Matrix expression representation. More...
#include <mat.hpp>
Related Functions | |
(Note that these are not member functions.) | |
CV_EXPORTS MatExpr | abs (const Mat &m) |
Calculates an absolute value of each matrix element. | |
CV_EXPORTS MatExpr | abs (const MatExpr &e) |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. |
Detailed Description
Matrix expression representation.
This is a list of implemented matrix operations that can be combined in arbitrary complex expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a real-valued scalar ( double )):
- Addition, subtraction, negation: `A+B`, `A-B`, `A+s`, `A-s`, `s+A`, `s-A`, `-A`
- Scaling: `A*alpha`
- Per-element multiplication and division: `A.mul(B)`, `A/B`, `alpha/A`
- Matrix multiplication: `A*B`
- Transposition: `A.t()` (means AT)
- Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems: `A.inv([method]) (~ A-1)`, `A.inv([method])*B (~ X: AX=B)`
- Comparison: `A cmpop B`, `A cmpop alpha`, `alpha cmpop A`, where *cmpop* is one of `>`, `>=`, `==`, `!=`, `<=`, `<`. The result of comparison is an 8-bit single channel mask whose elements are set to 255 (if the particular element or pair of elements satisfy the condition) or 0.
- Bitwise logical operations: `A logicop B`, `A logicop s`, `s logicop A`, `~A`, where *logicop* is one of `&`, `|`, `^`.
- Element-wise minimum and maximum: `min(A, B)`, `min(A, alpha)`, `max(A, B)`, `max(A, alpha)`
- Element-wise absolute value: `abs(A)`
- Cross-product, dot-product: `A.cross(B)`, `A.dot(B)`
- Any function of matrix or matrices and scalars that returns a matrix or a scalar, such as norm, mean, sum, countNonZero, trace, determinant, repeat, and others.
- Matrix initializers ( Mat::eye(), Mat::zeros(), Mat::ones() ), matrix comma-separated initializers, matrix constructors and operators that extract sub-matrices (see Mat description).
- Mat_<destination_type>() constructors to cast the result to the proper type.
- Note:
- Comma-separated initializers and probably some other operations may require additional explicit Mat() or Mat_<T>() constructor calls to resolve a possible ambiguity.
// compute pseudo-inverse of A, equivalent to A.inv(DECOMP_SVD) SVD svd(A); Mat pinvA = svd.vt.t()*Mat::diag(1./svd.w)*svd.u.t(); // compute the new vector of parameters in the Levenberg-Marquardt algorithm x -= (A.t()*A + lambda*Mat::eye(A.cols,A.cols,A.type())).inv(DECOMP_CHOLESKY)*(A.t()*err); // sharpen image using "unsharp mask" algorithm Mat blurred; double sigma = 1, threshold = 5, amount = 1; GaussianBlur(img, blurred, Size(), sigma, sigma); Mat lowContrastMask = abs(img - blurred) < threshold; Mat sharpened = img*(1+amount) + blurred*(-amount); img.copyTo(sharpened, lowContrastMask);
Definition at line 3281 of file mat.hpp.
Friends And Related Function Documentation
Calculates an absolute value of each matrix element.
abs is a meta-function that is expanded to one of absdiff or convertScaleAbs forms:
- C = abs(A-B) is equivalent to `absdiff(A, B, C)`
- C = abs(A) is equivalent to `absdiff(A, Scalar::all(0), C)`
- C = `Mat_<Vec<uchar,n> >(abs(A*alpha + beta))` is equivalent to `convertScaleAbs(A, C, alpha, beta)`
The output matrix has the same size and the same type as the input one except for the last case, where C is depth=CV_8U .
- Parameters:
-
m matrix.
- See also:
- MatrixExpressions, absdiff, convertScaleAbs
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