1 results listed
As is known, it is often difficult to store and
transmit images used in various computer applications. A
possible solution to this problem is to use one of the known data
compression techniques because they help to reconstruct the
image with a lower number of measurements. In this study, a
new Singular Value Decomposition (SVD)based technique is
proposed to compress images. The advantage of using SVD is
that it both has energy compression capability and is easily
adaptable to local statistical variations of the image.
Furthermore, the SVD can be implemented with non-square,
non-reversible matrices of size m x n. However, how to
determine the threshold value for image compression in the
SVD technique is still one of the fundamental problems. In this
study, the desired threshold value is calculated by dividing the
sum of the differences between the obtained singular values by
the rank of the matrix. Simulation results confirm the feasibility
of our proposed method.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
A. SUTCU
Ali Degirmenci
Ömer Karal
I. CANKAYA