A Hybrid Multi-focus Image Fusion Technique using SWT and PCA

Tushar Tyagi, Parth Gupta, Prabhishek Singh
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引用次数: 9

Abstract

This paper presents a new hybrid and parallel processing image fusion technique for multi-focus images. Here, two different methods are used i.e. Stationary Wavelet Transform (SWT) and Principal Component Analysis (PCA) that are implemented on the input images in parallel. These two methods are applied on same input dataset. This method is although computationally bit slower than the compared method but still it shows better results. The fused images obtained from the SWT and PCA are later again fused using PCA method. This is a parallel processing technique. The result of proposed method is compared with other traditional and conventional methods like DWT, SWT and PCA. It is observed that the result of proposed method is better than the compared methods. The result of the proposed method is analyzed qualitatively (visual appearance) and quantitatively using CC (Correlation Coefficient), UIQI (Universal Image Quality Index), and PSNR (Peak Signal-to-Noise Ratio). The proposed technique will have the capability to be implemented in real time applications of Visual Sensor Network (VSN).
基于SWT和PCA的混合多焦点图像融合技术
针对多聚焦图像,提出了一种新的混合并行处理图像融合技术。这里使用了两种不同的方法,即平稳小波变换(SWT)和主成分分析(PCA),它们并行地对输入图像进行处理。这两种方法应用于相同的输入数据集。该方法虽然在计算速度上比所比较的方法慢一些,但仍然显示出更好的结果。将SWT和PCA得到的融合后的图像再用PCA方法进行融合。这是一种并行处理技术。并将该方法与DWT、SWT、PCA等传统方法和常规方法进行了比较。结果表明,所提方法的计算结果优于对比方法。采用CC(相关系数)、UIQI(通用图像质量指数)和PSNR(峰值信噪比)对所提方法的结果进行定性(视觉外观)和定量分析。该技术可用于视觉传感器网络(VSN)的实时应用。
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