Difference between revisions of "Haar wavelet (2x2)"

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(New page: Original picture Haar transformation The two-dimensional Haar wavelet is useful for transforming data into 4 ...)
 
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The two-dimensional Haar wavelet is useful for transforming data into 4 bands where ''b0'' contains the DC level of each block while ''b1-b3'' contains higher frequency components.
 
The two-dimensional Haar wavelet is useful for transforming data into 4 bands where ''b0'' contains the DC level of each block while ''b1-b3'' contains higher frequency components.
  
By recursively applying the transformation on b0 until b0 reaches a size of 1 we get frequency information about different areas in the picture at different scales.
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By recursively applying the transformation on b0 until b0 reaches a size of 1 we get frequency information about different areas in the picture at different scales. After the transformations most values will have a low value (assuming that the input data is a normal photograph), by using quantization and setting very low values to zero the data will compress very well using fairly simple compression algorithms like Huffman.
  
 
  Input block of 2x2 pixels
 
  Input block of 2x2 pixels

Revision as of 03:12, 3 September 2007

Original picture
Haar transformation

The two-dimensional Haar wavelet is useful for transforming data into 4 bands where b0 contains the DC level of each block while b1-b3 contains higher frequency components.

By recursively applying the transformation on b0 until b0 reaches a size of 1 we get frequency information about different areas in the picture at different scales. After the transformations most values will have a low value (assuming that the input data is a normal photograph), by using quantization and setting very low values to zero the data will compress very well using fairly simple compression algorithms like Huffman.

Input block of 2x2 pixels
p0 p1
p2 p3
Forward transformation
b0 = (p0 + p1) + (p2 + p3)
b1 = (p0 - p1) + (p2 - p3)
b2 = (p0 + p1) - (p2 + p3)
b3 = (p0 - p1) - (p2 - p3)
Reverse transformation
p0 = ((b0 + b1) + (b2 + b3)) / 4
p1 = ((b0 - b1) + (b2 - b3)) / 4
p2 = ((b0 + b1) - (b2 + b3)) / 4
p3 = ((b0 - b1) - (b2 - b3)) / 4