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Efficient image fusion using visual salient features and cross-contrast with edge weakening guided image filter

机译:利用视觉显着特征进行有效的图像融合,并与边缘弱化引导图像滤波器进行交叉对比

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A novel algorithm determined by Nonsubsampled Contourlet Transform (NSCT) with edge weakening guided filter (EWGIF) is proposed during this paper by choosing and combining feature of the initial pictures. First of all initial pictures are break down into band pass and low subband coefficients by applying the nonsubsampled contourlet transform. Visible salience features is that the 1st picture that a viewer sees once staring at a picture, as an example, local energy, contrast and gradient are visual salience features. Lowpass subband coefficients are obtained by employing a visual salience feature whereas Band pass subband coefficients are acquired by using cross contrast. A cross-contrast method is got by calculating a ratio of the local mean of band-pass coefficients as well as local mean of lowpass coefficients which are solved by visual salience feature. Comparison tests are evaluated on various picture sets, and results outcome exhibit that the proposed technique performs better in both subjective and objective qualities.
机译:通过选择和组合初始图像的特征,提出了一种新的算法,该算法由非下采样轮廓波变换(NSCT)和边缘削弱导引滤波器(EWGIF)确定。首先,通过应用非子采样的contourlet变换,将初始图片分解为带通系数和低子带系数。可见的显着特征是观看者一看就看到的第一张图片,例如,局部能量,对比度和梯度是视觉上的显着特征。低通子带系数是通过使用视觉显着性特征获得的,而带通子带系数是通过使用交叉对比度获得的。通过计算通过视觉显着性特征求解的带通系数的局部均值与低通系数的局部均值之比,可以得到交叉对比方法。比较测试在各种图片集上进行评估,结果结果表明,所提出的技术在主观和客观质量上均表现更好。

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