Pattern-selective color image fusion

Abstract This paper introduces pattern-selective color image fusion and shows how it can be applied to two domains of image enhancement: extension of dynamic range and depth of focus. Pattern-selective fusion methods provide a mechanism for combining multiple monochromatic source images through identifying salient features in the source images at multiple scales and orientations, and combining those features into a single composite image result. In this paper, the pattern-selective fusion method is generalized into a framework that is equally applicable to monochrome, color, and multi-spectral imagery. This proposed fusion framework is then used to combine a set of color source images, taken from a sensor with varying aperture and focus settings, into a single fused image result that has improved dynamic range and depth of field over any of the other frames in the input sequence. Experimental results show the performance of the dynamic range and depth-of-field extension on imagery taken from consumer-grade video camera equipment.