Karteikarten: Fundamentals of Image Processing and Transformations — 23 Karten

Vectors — notation?

Bold lowercase letters, e.g., v.

Matrices — notation?

Bold uppercase letters, e.g., A.

Complex conjugation — symbol?

Asterisk (*).

Hadamard product — meaning?

Element-wise multiplication.

Image function — domain?

Spatial coordinates Ω.

Discrete images — representation?

Pixel grid as matrices or arrays.

Coordinate system — origin?

Typically at upper-left pixel.

Visualization methods?

Matrix view, color image, surface, profile.

Discretization — steps?

Sampling (domain), quantization (range).

Interpolation — purpose?

Estimate pixel values at non-grid points.

Linear transformation — property?

Preserves addition and scalar multiplication.

Shift invariance — property?

Response independent of position.

Affine transformation — components?

Linear + translation.

Image resolution — determines?

Detail level and spatial clarity.

Contrast — formula?

(Imax - Imin)/(Imax + Imin).

Noise — model?

Additive random component.

Memory footprint — calculation?

Width × Height × bits per pixel.

Coordinate transformation — role?

Convert pixel to physical coordinates.

Surface plot — shows?

Intensity as height in 3D.

Separable kernel — advantage?

Reduced computation via 1D operations.

Homogeneous coordinates — use?

Represent affine transforms as matrices.

Geometric transformation — example?

Rotation, scaling, translation.

Image characteristics — include?

Resolution, contrast, noise, size.