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首页> 外文期刊>International Journal of Engineering Research and Applications >Development of Image Fusion Algorithm for Impulse Noise Removal inDigital Images using the quality Assessment in Spatial Domain
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Development of Image Fusion Algorithm for Impulse Noise Removal inDigital Images using the quality Assessment in Spatial Domain

机译：基于空间域质量评估的数字图像脉冲噪声消除图像融合算法的开发

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摘要

Now a days remote sensing plays very important role in satellite based communication. Satellite gives images in digital format. Digital images are often corrupted during acquisition, transmission or due to faulty memory locations in hardware. The noise density varies depending on various factors namely reflective surfaces, atmospheric variations, noisy communication channels etc. Impulse noise corruption is very common in digital images. In this paper, the images captured by different sensors, producing different impulse noisy images are considered. As order statistics filters exhibit better performance, these noisy images are filtered individually using non linear filtering algorithms namely, Vector Median Filter (VMF), Rank Conditioned VMF, Rank conditioned and Threshold VMF, Center Weighted VMF and Absolute Deviation VMF. These filtered images are combined to a single image called image fusion, which retains the important features of the images from individual sensors. The filtered images are fused into a single image by using the image fusion technique which is based on the quality assessment in spatial domain. Now this fused image is again filtered using absolute deviation VMF which performs better than fused image. The performance evaluation of the filtered and the fused image with respect to the original image is done using mean square error(MSE), peak signal to noise ratio(PSNR) and structural similarity index(SSIM).
机译：如今，遥感在基于卫星的通信中扮演着非常重要的角色。卫星提供数字格式的图像。数字图像通常在采集，传输或硬件中错误的存储位置时损坏。噪声密度取决于各种因素，即反射面，大气变化，嘈杂的通信通道等。脉冲噪声损坏在数字图像中非常常见。在本文中，考虑了由不同传感器捕获的图像，产生了不同的脉冲噪声图像。由于阶次统计滤波器表现出更好的性能，这些噪点图像将使用非线性滤波算法（向量中值滤波器（VMF），秩条件VMF，秩条件和阈值VMF，中心加权VMF和绝对偏差VMF）分别进行滤波。这些经过过滤的图像被组合为一个称为图像融合的图像，该图像保留了来自各个传感器的图像的重要特征。使用基于空间域质量评估的图像融合技术将滤波后的图像融合为单个图像。现在，该融合图像再次使用绝对偏差VMF进行滤波，其绝对性能优于融合图像。使用均方误差（MSE），峰值信噪比（PSNR）和结构相似性指标（SSIM）对滤波后的图像和融合后的图像相对于原始图像进行性能评估。

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