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FPGA implementation of satellite image fusion using wavelet substitution method

机译:小波替换法在卫星图像融合中的FPGA实现

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Image fusion is a process of merging the relevant information from a set of images into a single image. The goal of image fusion in remote sensing is to create new images that contain both low spatial resolution multispectral data (color information) and high spatial resolution panchromatic data (details). The choice of appropriate wavelet filters for the design and implementation on FPGA, a detailed analysis has been carried out in MATLAB Simulink R2010b software using averaging, additive and substitutive fusion rules. In this paper substitutive rule using the Haar, Daubechies 3 (db3) and Cohen Daubechies Feauveau (CDF) 9/7 filters are used for image decomposition and reconstruction. CDF 9/7 is found to be the best filter and is chosen for FPGA implementation. Single level 2D-DWT based image fusion has been performed using substitutive method and then the hardware software co-simulation design has been synthesized in Xilinx ISE 13.1 and implemented on ML605 Virtex 6 FPGA kit. From the results, it is observed that the design consumes a total power of 4.349W and operates at a maximum frequency of 849.618MHz.
机译:图像融合是将一组图像中的相关信息合并为单个图像的过程。遥感图像融合的目标是创建包含低空间分辨率多光谱数据(颜色信息)和高空间分辨率全色数据(细节)的新图像。为在FPGA上进行设计和实现选择合适的小波滤波器,已在MATLAB Simulink R2010b软件中使用平均,加法和置换融合规则进行了详细分析。在本文中,使用Haar,Daubechies 3(db3)和Cohen Daubechies Feauveau(CDF)9/7滤镜的替换规则用于图像分解和重建。发现CDF 9/7是最好的滤波器,并被选择用于FPGA实现。使用替代方法进行了基于单级2D-DWT的图像融合,然后在Xilinx ISE 13.1中综合了硬件软件协同仿真设计,并在ML605 Virtex 6 FPGA套件上实现了该仿真。从结果可以看出,该设计消耗的总功率为4.349W,最大工作频率为849.618MHz。

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