CS654: Digital Image Analysis Lecture 11: Image Transforms.

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Presentation transcript:

CS654: Digital Image Analysis Lecture 11: Image Transforms

Recap of Lecture 10 B-Spline curve Constant, Linear, Quadratic, Cubic interpolation Nearest neighbour, Bi-Linear, Bi-Cubic interpolation

Outline of Lecture 11 Image transforms Unitary matrices 1-D and 2-D unitary transforms

Introduction Input ImageOutput Image Forward transform Reverse transform N N N N Applications Filtering – removing higher or lower frequency component Data Compression – storage space and transmission bandwidth Feature extraction

Example Image: Digital Image Processing, 3rd Edition, Gonzalez and Woods Input Image Magnitude of the Fourier Transform Mask to eliminate energy bursts Output Image

General Approach Image: Digital Image Processing, 3rd Edition, Gonzalez and Woods

Definition It refers to a class of unitary matrices used for representing images Similarly to 1-D basis functions, an image can be represented with the help of basis images The basis images can be generated using unitary matrices An image transform provides a set of basis vector the vector space

Unitary Matrix Example: As transformations they preserve length, and preserve the angle between vectors.

1-D Representation For an one dimensional sequence A unitary transformation is written as: Series representation Or, Series representation Or, Basis vector of A

2-D Orthogonal Unitary Transforms Inverse transform Complete, orthonormal, discrete basis functions

Properties of Basis functions

Transformed Image The set V denotes the transformed image

Truncated series summation Sum of squared Error Error will be minimum if

Computational complexity

Thank you Next Lecture: Image transformations-II