Computer Vision Foundations · free preview

Analysis and Synthesis

Every image transform is a pair of matrices, one that projects the image onto templates and one that rebuilds the image from coefficients.

1. The last lesson and a new frame

The last lesson and a new frame

2. Three sampling regimes

Three sampling regimes

3. Self-inverting transforms

Self-inverting transforms

4. A map of what follows

A map of what follows

5. Which regime

A transform analyzes a 256-pixel image into 1024 coefficients using templates stacked in a tall matrix P\mathbf{P}. The analysis is complete, meaning suitable coefficient vectors can rebuild any image. Which statement is correct?

6. Self-inverting round trip

A self-inverting transform satisfies PPT=I\mathbf{P}\mathbf{P}^T = \mathbf{I}. An image goes through analysis r=PTℓ\mathbf{r} = \mathbf{P}^T\boldsymbol{\ell} and then synthesis with Q=P\mathbf{Q} = \mathbf{P}. What is the reconstructed image, and what does PTP\mathbf{P}^T\mathbf{P} equal in general?

7. Round trip error

A self-inverting transform has PPT=I\mathbf{P}\mathbf{P}^T = \mathbf{I}. An image ℓ\boldsymbol{\ell} is analyzed to coefficients r=PTℓ\mathbf{r} = \mathbf{P}^T\boldsymbol{\ell} and synthesized back with Q=P\mathbf{Q} = \mathbf{P}. Compute the squared reconstruction error ∥Pr−ℓ∥2\|\mathbf{P}\mathbf{r} - \boldsymbol{\ell}\|^2 and write it as a number.

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