基于多变换的多聚焦图像融合算法

Nirmala Paramanandham, Kishore Rajendiran, Deepika Narayanan, Indu Vadhani S, Mrinalini Anand
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引用次数: 12

摘要

图像融合是将同一场景的多幅源图像整合为一幅图像,同时保留每张图像的重要和显著特征的过程。所得到的融合图像提供了比任何单个源图像更准确的描述。本文将离散小波变换与平稳小波变换相结合,提出了一种新的多焦点图像融合方法。利用小波变换对源图像进行分解,并根据融合规则对系数进行融合。通过对融合系数进行小波反变换,得到信息丰富的融合图像。采用RMSE、PSNR、SF和Entropy等参数对该框架进行了评价。仿真结果从定量和主观上都证明了所提出的融合方法是有效的,在多聚焦图像的融合方面比现有的传统单变换方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient multi transform based fusion for multi focus images
Image fusion is the process of integrating multiple source images of the same scene into a single image, retaining the important and salient features from each image. The resultant fused image provides a more accurate description than any of the individual source images. In this paper a novel multi focus image fusion method is presented by combining Discrete Wavelet Transform and Stationary Wavelet Transform. The source images are decomposed using wavelet transforms and the coefficients are fused according to the fusion rule. An informative fused image is obtained by performing the inverse wavelet transforms to the fused coefficients. The proposed framework is evaluated by employing parameters such as RMSE, PSNR, SF and Entropy. The simulation results demonstrate both quantitatively and subjectively that the proposed fusion approach is effective and can provide better performance in fusing multi-focus images than other conventional state of art single transform methods in the literature.
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