Article ID Journal Published Year Pages File Type
406681 Neurocomputing 2014 17 Pages PDF
Abstract

•A new framework based on region reconstruction is proposed for multifocus fusion.•We propose an efficient greedy optimization algorithm with a coarse-to-fine strategy.•The visual artifacts are explicitly modeled by three energy terms in our model.•Our method outperforms the state-of-the-art methods in various experiments.

This paper presents a novel region-based framework for multifocus image fusion. The core idea is to segment the in-focus regions from the input images and merge them up to produce an all-in-focus image. To this end, we propose three intuitive constraints on the fusion process and model them into three energy terms, i.e., reconstruction error, out-of-focus energy and smoothness regularization. The three terms are then formulated into an optimization framework problem to solve a segmentation map. We also propose a greedy algorithm to minimize the objective function, which alternatively updates each pixel in the segmentation map using a coarse-to-fine strategy. The fused image is finally generated by combining the segmented in-focus regions in each source image via the segmentation map. Our approach can yield a seamless result with much fewer ringing artifacts. Comparative experiments based on various synthesized and real images demonstrate that our approach outperforms the state-of-the-art methods.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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