International Journal of Computational
Intelligence Research (IJCIR)
Volume 2, Number 4 (2006)
Nonlinear image enhancement to improve face detection in complex
Li Tao, Ming-Jung Seow, Vijayan K. Asari
Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University, Norfolk, VA 23529 USA
A robust and efficient image enhancement technique has been developed to improve the visual quality of digital images that exhibit dark shadows due to the limited dynamic ranges of imaging and display devices which are incapable of handling high dynamic range scenes. The proposed technique processes images in two separate steps: dynamic range compression and local contrast enhancement. Dynamic range compression is a neighborhood dependent intensity transformation which is able to enhance the luminance in dark shadows while keeping the overall tonality consistent with that of the input image. The image visibility can be largely and properly improved without creating unnatural rendition in this manner. A neighborhood dependent local contrast enhancement method is used to enhance the images contrast following the dynamic range compression. Experimental results on the proposed image enhancement technique demonstrates strong capability to improve the performance of convolutional face finder compared to histogram equalization and multiscale Retinex with color restoration without compromising the false alarm rate.
image enhancement, face detection, dynamic range compression, luminance enhancement, contrast enhancement.