An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving

• Main Authors: Jing Rui Tang, Nor Ashidi Mat Isa
• Format: Article
• Language: English
• Published: ITB Journal Publisher 2015-01-01
• Series: Journal of ICT Research and Applications
• Online Access: http://journals.itb.ac.id/index.php/jictra/article/view/697

<span>This paper modifies the Adaptive Contrast Enhancement Algorithm<br /><span>with Details Preserving (ACEDP) technique by integrating a fuzzy element in<br /><span>the image type selection. The proposed technique, named the Adaptive Fuzzy<br /><span>Contrast Enhancement with Details Preserving (AFCEDP) technique, first<br /><span>computes the degree of membership of the input image to three categories, i.e.<br /><span>low-, middle- or high-level images. The AFCEDP technique then clips the<br /><span>histogram at different plateau limits that are computed from both the degree of<br /><span>membership and the clipping functions. The classification of an image in the<br /><span>ACEDP technique is done based solely on the intensity range of the maximum<br /><span>number of pixels, which may be inaccurate. In the proposed AFCEDP technique,<br /><span>the image type classification is handled in a better way with the integration of a<br /><span>fuzzy element. The performance of the proposed AFCEDP technique was<br /><span>compared with the conventional ACEDP technique and several state-of-art<br /><span>techniques described in the literature. The simulation results revealed that the<br /><span>AFCEDP technique demonstrates good capability in contrast enhancement and<br /><span>detail preservation. In addition, the experiments using cervical cell images and<br /><span>HEp-2 cell images showed great potential of the AFCEDP technique as a<br /><span>technique for enhancing medical microscopic images.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br class="Apple-interchange-newline" /></span>