The remote-sensed images may be degraded by some factors during their obtaining. It decreases the quality of the
images and becomes an obstacle of the image recognition. So it's very necessary to restore the degraded image. At
present, most of the image restoration algorithms are depended on the priori knowledge or a given physical model of the
image degeneration. The paper presents a new algorithm for remote-sensed image restoration based on gene expression
programming (GEP). The paper needs a reference image at first; then applies the GEP to mine the math function
between reference image and degraded image; at last, restores the degraded image with the math function. The
experiment results demonstrate that the method is effective and practical.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.