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  2. LMS color space - Wikipedia

    en.wikipedia.org/wiki/LMS_color_space

    The Hunt and RLAB color appearance models use the Hunt–Pointer–Estevez transformation matrix (M HPE) for conversion from CIE XYZ to LMS. [4] [5] [6] This is the transformation matrix which was originally used in conjunction with the von Kries transform method, and is therefore also called von Kries transformation matrix (M vonKries).

  3. Projective texture mapping - Wikipedia

    en.wikipedia.org/wiki/Projective_texture_mapping

    Historically, using projective texture mapping involved considering a special form of eye linear texture coordinate generation transform (tcGen for short). This transform was then multiplied by another matrix representing the projector's properties which were stored in texture coordinate transform matrix. The resulting concentrated matrix was ...

  4. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    If is a linear transformation mapping to and is a column vector with entries, then = for some matrix , called the transformation matrix of . [ citation needed ] Note that A {\displaystyle A} has m {\displaystyle m} rows and n {\displaystyle n} columns, whereas the transformation T {\displaystyle T} is from R n {\displaystyle \mathbb {R} ^{n ...

  5. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    For example, for the 2×2 matrix = [], the half-vectorization is ⁡ = []. There exist unique matrices transforming the half-vectorization of a matrix to its vectorization and vice versa called, respectively, the duplication matrix and the elimination matrix .

  6. Image rectification - Wikipedia

    en.wikipedia.org/wiki/Image_rectification

    In this example, we simply define H' using the rotation matrix R and initial projective transformation H as ′ =. Finally, we scale both images to the same approximate resolution and align the now horizontal epipoles for easier horizontal scanning for correspondences (row 4 of 2D image set).

  7. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    For example, the 4 × 4 matrix in the example above has rank three. Because the column space is the image of the corresponding matrix transformation, the rank of a matrix is the same as the dimension of the image.

  8. Rotation matrix - Wikipedia

    en.wikipedia.org/wiki/Rotation_matrix

    Noting that any identity matrix is a rotation matrix, and that matrix multiplication is associative, we may summarize all these properties by saying that the n × n rotation matrices form a group, which for n > 2 is non-abelian, called a special orthogonal group, and denoted by SO(n), SO(n,R), SO n, or SO n (R), the group of n × n rotation ...

  9. 3D projection - Wikipedia

    en.wikipedia.org/wiki/3D_projection

    If the normal of the viewing plane (the camera direction) is parallel to one of the primary axes (which is the x, y, or z axis), the mathematical transformation is as follows; To project the 3D point , , onto the 2D point , using an orthographic projection parallel to the y axis (where positive y represents forward direction - profile view ...