Color image enhancement based on particle swarm optimization with Gaussian mixture

Shibudas Kattakkalil Subhashdas; Bong-Seok Choi; Ji-Hoon Yoo; Yeong-Ho Ha

doi:10.1117/12.2077381

8 February 2015 Color image enhancement based on particle swarm optimization with Gaussian mixture

Shibudas Kattakkalil Subhashdas, Bong-Seok Choi, Ji-Hoon Yoo, Yeong-Ho Ha

Proceedings Volume 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications; 939508 (2015) https://doi.org/10.1117/12.2077381
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

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.

Citation Download Citation

Shibudas Kattakkalil Subhashdas, Bong-Seok Choi, Ji-Hoon Yoo, and Yeong-Ho Ha "Color image enhancement based on particle swarm optimization with Gaussian mixture", Proc. SPIE 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications, 939508 (8 February 2015); https://doi.org/10.1117/12.2077381

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available