What Do Skewness and Kurtosis Represent? I understand that the question could mean a lot of things but I am thinking specifically to image processing. For example, I know that the mean can be a basic texture feature that represents the average pixel value of the image. That is, it is useful for determining an image background. Then I know that the standard deviation can be an indicator of how spread is the histogram and is useful for indicating what other pixel values also belong to the background. 

In similar terms to this, what do Kurtosis and Skewness represent? I have read about them in various posts but I can't find anything related to what they represent in terms of what I have explained above.

I am not sure if I have came to the right place but if I haven't feel free to point me in the right direction.
This paper has a nice write up on those and many other measures.

For skewness:


  In terms of digital image processing, Darker and
  glossier surfaces tend to be more positively skewed than
  lighter and matte surfaces. Hence we can use skewness in
  making judgements about image surfaces. 


This is because skewness measures how "lopsided" the distribution of pixel values are.   

For kurtosis:


  In digital image processing kurtosis values are
  interpreted in combination with noise and resolution
  measurement. High kurtosis values should go hand in
  hand with low noise and low resolution. 


I'm not sure I agree with this.  Images with moderate amounts of salt and pepper noise are likely to have a high kurtosis value.