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An effective infrared and visible image fusion algorithm restraining noise

机译:一种有效的抑制噪声的红外与可见光图像融合算法

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摘要

For the low infrared image contrast and high background noise, we proposed a new image fusion algorithm based on lifting stationary wavelet multi-scale product. The high-frequency coefficient option based on edges gradient energy was proposed based on lifting stationary wavelet multi-scale product, which makes full use of multi-scale product features with enhancing edges structure while weakening image noise; The weighted method was used for low-frequency coefficients fusion. Then wavelet transform reconstruction was realized to get the final fused image. Experimental results show that the algorithm can better protect edge features and all the useful information of the source images while restraining noise. The better visual effects are gained compared with the traditional fusion methods.
机译:针对红外图像对比度低,背景噪声高的问题,提出了一种基于提升平稳小波多尺度积的图像融合算法。在提升固定小波多尺度产品的基础上,提出了一种基于边缘梯度能量的高频系数选择方法,该方法充分利用了多尺度产品的特征,既增强了边缘结构,又降低了图像噪声。加权方法用于低频系数融合。然后实现小波变换重构,得到最终的融合图像。实验结果表明,该算法在抑制噪声的同时,可以更好地保护边缘特征和源图像的所有有用信息。与传统的融合方法相比,可以获得更好的视觉效果。

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