In this paper, we propose a novel method to enhance low quality images. Specifically, we focus on facial images. Low quality images are often degraded by motion artifacts, sensor limitations, and noise contamination leading to loss of higher order information that is essential for face recognition. First, we demonstrate that conventional denoising and deblurring methods are not able to fully recover the latent image resulting in residual artifacts in the image. Then, we present a novel approach for image enhancement that removes these residual artifacts using sparse encoding methods. The potential of the method is demonstrated through promising results on facial images for face recognition application.
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E. Bilgazyev ; U. Kurkure ; S. K. Shah and I. A. Kakadiaris
ASIE: application-specific image enhancement for face recognition
", Proc. SPIE 8712, Biometric and Surveillance Technology for Human and Activity Identification X, 87120U (May 31, 2013); doi:10.1117/12.2019021; http://dx.doi.org/10.1117/12.2019021