Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A Histogram Adaptation for Contrast Enhancement


Affiliations
1 Department of Electronics and Communication, Anna University of Technology, Coimbatore, India
     

   Subscribe/Renew Journal


Histogram equalization is the common methods used for improving contrast in image processing application. But this technique is not well suited for implementation in consumer electronics such as television as it introduces unnecessary visual deterioration such as the saturation effect. It causes changes in the brightness of the input image. Thus, for the implementation of contrast enhancement it should be able to maintain the original input brightness in the output image. By adjusting the input histogram, input brightness can be preserved. The adjusted histogram can then be accumulated to map input pixels to output pixels. By introducing designed penalty terms, the level of contrast enhancement can be adjusted. Thus it is possible to generate a modified histogram which is closer to uniform histogram. Experimental results show a comparison of various quantitative measurements.

Keywords

Contrast Enhancement, Histogram Equalization, Histogram Modification, Image Processing.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 286

PDF Views: 2




  • A Histogram Adaptation for Contrast Enhancement

Abstract Views: 286  |  PDF Views: 2

Authors

Lisha Thomas
Department of Electronics and Communication, Anna University of Technology, Coimbatore, India
K. Santhi
Department of Electronics and Communication, Anna University of Technology, Coimbatore, India

Abstract


Histogram equalization is the common methods used for improving contrast in image processing application. But this technique is not well suited for implementation in consumer electronics such as television as it introduces unnecessary visual deterioration such as the saturation effect. It causes changes in the brightness of the input image. Thus, for the implementation of contrast enhancement it should be able to maintain the original input brightness in the output image. By adjusting the input histogram, input brightness can be preserved. The adjusted histogram can then be accumulated to map input pixels to output pixels. By introducing designed penalty terms, the level of contrast enhancement can be adjusted. Thus it is possible to generate a modified histogram which is closer to uniform histogram. Experimental results show a comparison of various quantitative measurements.

Keywords


Contrast Enhancement, Histogram Equalization, Histogram Modification, Image Processing.