
- •Image Interpolation
- •Introduction
- •A Sentimental Comment
- •Engineering Motivations
- •Scenario I: Resolution
- •Scenario II: Image Inpainting
- •Scenario III: Image Warping
- •Image Interpolation
- •1D Zero-order (Replication)
- •1D First-order Interpolation (Linear)
- •Linear Interpolation Formula
- •Numerical Examples
- •1D Third-order Interpolation (Cubic)*
- •From 1D to 2D
- •Graphical Interpretation
- •Numerical Examples
- •Numerical Examples (Con’t)
- •Bicubic Interpolation*
- •Limitation with bilinear/bicubic
- •Edge-Sensitive Interpolation
- •NEDI Step 1: Interpolate
- •NEDI Step 2: Interpolate the
- •Geometric Duality
- •Image Interpolation
- •Pixel Replication
- •Bilinear Interpolation
- •Bicubic Interpolation
- •Edge-Directed Interpolation
- •Image Demosaicing
- •Image Example
- •Error Concealment*
- •Image Inpainting*
- •Image Mosaicing*
- •Geometric Transformation
- •Basic Principle
- •Rotation
- •MATLAB Example
- •Rotation Example
- •Scale
- •Affine Transform
- •Affine Transform Example
- •Shear
- •Shear Example
- •Projective Transform
- •Projective Transform Example
- •Polar Transform
- •Iris Image Unwrapping
- •Use Your Imagination
- •Free Form Deformation
- •Application into Image Metamorphosis
- •Summary of Image

NEDI Step 1: Interpolate
diagonal pixels*
1 |
4 |
0
1
4
0
2
2
3
3
Implementation:
-Formulate LS estimation problem with pixels at low resolution and solve {a1,a2,a3,a4}
-Use {a1,a2,a3,a4} to
interpolate the pixel
0 at the high resolution
Please refer to sri1.m in interp.zip
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NEDI Step 2: Interpolate the |
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Other Half* |
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Implementation: |
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-Formulate LS estimation |
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problem with pixels at |
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4 |
low resolution and solve |
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{a1,a2,a3,a4} |
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-Use {a1,a2,a3,a4} to |
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interpolate the pixel |
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0 at the high resolution |
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Please refer to sri2.m in interp.zip
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Geometric Duality
Step-I |
Step-I after rotation |
Step-II |
of 45-degree |
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Image Processing |
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Image Interpolation
• Introduction
• Interpolation Techniques
– 1D zero-order, first-order, third-order
– 2D zero-order, first-order, third-order
– Directional interpolation*
• Interpolation Applications
– Digital zooming (resolution enhancement) |
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– Image inpainting (error concealment) |
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– Geometric transformations (where your |
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imagination can fly) |
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Image Processing |
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Pixel Replication
low-resolution image (100×100)
high-resolution image (400×400)
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Image Processing |
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Bilinear Interpolation
low-resolution image (100×100)
high-resolution image (400×400)
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Image Processing |
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Bicubic Interpolation
low-resolution image (100×100)
high-resolution image (400×400)
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Image Processing |
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Edge-Directed Interpolation
(Li&Orchard’2000)
low-resolution image (100×100)
high-resolution
image (400×400)
EE465: Introduction to Digital 28 Image Processing



Image Demosaicing
(Color-Filter-Array Interpolation)
Bayer Pattern
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Image Processing |
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Image Example
Ad-hoc CFA Interpolation |
Advanced CFA Interpolation |
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Image Processing |
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