This paper proposes a Gaussian mixture based image enhancement method which uses particle swarm optimization
(PSO) to have an edge over other contemporary methods. The proposed method uses the guassian mixture model to
model the lightness histogram of the input image in CIEL*a*b* space. The intersection points of the guassian
components in the model are used to partition the lightness histogram. . The enhanced lightness image is generated by
transforming the lightness value in each interval to appropriate output interval according to the transformation function
that depends on PSO optimized parameters, weight and standard deviation of Gaussian component and cumulative
distribution of the input histogram interval. In addition, chroma compensation is applied to the resulting image to reduce
washout appearance. Experimental results show that the proposed method produces a better enhanced image compared to
the traditional methods. Moreover, the enhanced image is free from several side effects such as washout appearance,
information loss and gradation artifacts.
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.