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00:00:00
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Lecture 3: Linear Filters |
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00:01:42
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Demo "Haribo Classification" |
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00:03:15
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You Can Do It At Home... |
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00:04:48
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Course Outline |
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00:05:29
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Motivation |
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00:05:55
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Topics of This Lecture |
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00:07:03
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Common Types of Noise |
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00:11:50
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Gaussian Noise |
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00:12:50
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First Attempt at a Solution |
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00:13:59
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Moving Average in 2D |
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00:15:12
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Correlation Filtering |
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00:18:25
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Convolution |
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00:20:06
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Correlation vs. Convolution |
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00:21:46
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Shift Invariant Linear System |
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00:23:27
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Properties of Convolution |
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00:27:44
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Averaging Filter |
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00:28:57
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Smoothing by Averaging |
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00:31:42
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Smoothing with a Gaussian |
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00:33:04
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Gaussian Smoothing |
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00:35:30
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Gaussian Smoothing: variance |
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00:36:39
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Gaussian Smoothing: kernel size |
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00:39:49
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Gaussian Smoothing in Matlab |
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00:41:22
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Effect of Smoothing |
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00:42:56
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Efficient Implementation |
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00:45:33
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Filtering: Boundary Issues |
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00:47:11
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Filtering: Boundary Issues: Methods |
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00:52:44
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Filtering: Boundary Issues: Methods (MATLAB) |
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00:53:48
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Topics of This Lecture |
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00:54:21
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Why Does This Work? |
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00:57:21
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The Fourier Transform in Cartoons |
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00:58:22
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Fourier Transforms of Important Functions |
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01:02:45
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Duality |
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01:04:27
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Effect of Convolution |
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01:06:38
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Effect of Filtering |
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01:11:06
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Low-Pass vs. High-Pass |
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01:14:22
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Quiz: What Effect Does This Filter Have? |
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01:15:21
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Sharpening Filter |
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01:16:51
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Application: High Frequency Emphasis |
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01:18:56
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Topics of This Lecture |
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01:19:11
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Non-Linear Filters: Median Filter |
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01:20:26
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Median Filter |
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01:20:53
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Median Filter: edge preserving |
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01:21:46
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Median vs. Gaussian Filtering |
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01:24:33
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Topics of This Lecture |
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01:24:49
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Motivation: Fast Search Across Scales |
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01:25:44
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Image Pyramid |
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01:26:03
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How Should We Go About Sampling? |
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01:28:11
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Fourier Interpretation: Discrete Sampling |
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01:29:58
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Sampling and Aliasing |
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01:31:20
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Sampling and Aliasing: Nyquist theorem |
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01:32:51
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Aliasing in Graphics |
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01:33:09
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Resampling with Prior Smoothing |
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01:34:37
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References and Further Reading |