Image compression


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Image compression

  1. 1. ImageCompression<br />
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  3. 3. Basis<br /><ul><li> A set of linearly independent vectors whose linear combination can be used to express any vector in a given vector space (In our case, the vector space is the 8 x 8 matrix, X). There can be infinitely many bases for a given vector space. So, for representing our image, we are free to choose any basis that is convenient to us. The coefficient matrix will vary accordingly. ( Since X = BC and C = B-1X)
  4. 4. B = [ b0 | b1 | b2 | b3 | b4 | b5 | b6 | b7 ] where b0, b1,.., b7 are 8 x 1 linearly independent vectors.
  5. 5. A “Good” basis should have more of low frequency vectors or bis (ideal: all ones in the column; imply less variation of pixel values in space) and very few high frequency vectors (alternate +1s and -1s; imply maximum variation of pixel values in space) in order to account for the general smoothness of images.</li></li></ul><li>Bases To Choose From<br />‘w’ in Fourier Basis is the nth root of unity for a basis of dimension n x n.<br />
  6. 6. Choice of Basis<br />
  7. 7. What makes a basis good?<br />
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  10. 10. Reference<br />MIT OCW: Linear Algebra (Gilbert Strang) Lecture 31<br />MIT OCW: Linear Algebra (Gilbert Strang) Lecture 26<br /><br /><br /><br /><br />