  Singular Value Decomposition (SVD) has recently emerged as a new paradigm for
processing different types of images. SVD is an attractive algebraic transform
for image processing applications. The paper proposes an experimental survey
for the SVD as an efficient transform in image processing applications. Despite
the well-known fact that SVD offers attractive properties in imaging, the
exploring of using its properties in various image applications is currently at
its infancy. Since the SVD has many attractive properties have not been
utilized, this paper contributes in using these generous properties in newly
image applications and gives a highly recommendation for more research
challenges. In this paper, the SVD properties for images are experimentally
presented to be utilized in developing new SVD-based image processing
applications. The paper offers survey on the developed SVD based image
applications. The paper also proposes some new contributions that were
originated from SVD properties analysis in different image processing. The aim
of this paper is to provide a better understanding of the SVD in image
processing and identify important various applications and open research
directions in this increasingly important area; SVD based image processing in
the future research.
