Scale space implementation | Wikipedia audio article
Channel: wikipedia tts
Date: 2019-05-17

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Scale_space_implementation


00:03:33 1 Separability
00:07:59 2 The sampled Gaussian kernel
00:12:28 3 The discrete Gaussian kernel
00:18:02 4 Recursive filters
00:25:53 5 Finite-impulse-response (FIR) smoothers
00:26:26 6 Real-time implementation within pyramids and discrete approximation of scale-normalized derivatives
00:27:14 7 Other multi-scale approaches
00:31:22 8 See also
00:32:40 9 References
00:34:07 See also



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SUMMARY
=======
The linear scale-space representation of an N-dimensional continuous signal,

  
    
      
        
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    {\displaystyle f_{C}\left(x_{1},\cdots ,x_{N},t\right),}
  is obtained by convolving fC with an N-dimensional Gaussian kernel:

  
    
      
        
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    {\displaystyle g_{N}\left(x_{1},\cdots ,x_{N},t\right).}
  In other words:

  
    
      
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    {\displaystyle L\left(x_{1},\cdots ,x_{N},t\right)=\int _{u_{1}=-\infty }^{\infty }\cdots \int _{u_{N}=-\infty }^{\infty }f_{C}\left(x_{1}-u_{1},\cdots ,x_{N}-u_{N},t\right)\cdot g_{N}\left(u_{1},\cdots ...