Color Shift Model-Based Segmentation and Fusion for Digital Autofocusing

Abstract

This paper proposes a novel color shift model-based segmentation and fusion algorithm for digital autofocusing of color images. The source images are obtained using new multiple filter-aperture configurations. We shift color channels to change the focal point of the given image at different locations. For each respective location we then select the optimal focus information and, finally, use soft decision fusion and blending (SDFB) to obtain fully-focused images. The proposed autofocusing algorithm consists of: (i) color channel shifting and alignment for varying focal positions; (ii) optimal focus region selection and segmentation using sum modified Laplacian (SML); and (iii) SDFB, which enables smooth transition across region boundaries. By utilizing segmented images for different focal point locations, the SDFB algorithm can combine images with multiple, out-of-focus objects. Experimental results show performance and feasibility of the proposed algorithm for autofocusing images with one or more differently out-of-focus objects.