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Analysis of synthetic aperture radar image enchancement algorithm

机译:合成孔径雷达图像增强算法分析

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Most airborne and orbital SAR systems are monostatic, in that they employ a single antenna for transmission and reception of the radar signal. In optics, an imaging lens applies a phase function to a scattered field so that coherent summation occurs at the correct location in the image plane. Areas of current research and development include foliage penetration, ground penetration, imaging moving vehicles, bistatic imaging and techniques for improved image quality. Synthetic aperture radar imaging provides high resolution images of large areas. The intensities of pixels in a SAR image are based on the spatial orientation, roughness, and dielectric constant of the surface imaged. SAR is an active sensor, transmitting its own energy, and then measuring the return scattered by the earth's surface back to the satellite's antenna. SAR processing is the transformation of raw SAR signal data into a spatial image Due to the imaging mechanism, Synthetic Aperture Radar (SAR) images are susceptible to speckle noise, which affects radar image interpretation. So image enhancement is important topic of improves SAR image clarity. A nonlinear image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) is proposed in this paper. The image is decomposed into coefficients of different scales and directions through nonsubsampled contourlet transform. It is denoised by the threshold method of the multi-scale product of NSCT coefficients. Then thresholds of the nonlinear enhancement function are determined according to the coefficients of each scale. The two parameters of the function, among which one is used to control the range of enhancement and the other can determine the strength of enhancement, are obtained by solving nonlinear equations. The coefficients processed by the enhancement function are used to reconstruct the image. The simulation results on the Matlab platform show that the algorithm has a good effect of enhancing details of images and suppressing noise signals meanwhile.
机译:大多数机载和轨道SAR系统都是单基地的,因为它们使用单​​个天线来发送和接收雷达信号。在光学中,成像透镜将相位函数应用于散射场,以便相干求和发生在像平面中的正确位置。当前的研究和开发领域包括树叶穿透,地面穿透,移动车辆成像,双基地成像和提高图像质量的技术。合成孔径雷达成像可提供大面积的高分辨率图像。 SAR图像中像素的强度基于所成像表面的空间方向,粗糙度和介电常数。 SAR是一个主动传感器,它传输自身的能量,然后测量由地球表面散射回卫星天线的返回信号。 SAR处理是将原始SAR信号数据转换为空间图像由于成像机制,合成孔径雷达(SAR)图像易受斑点噪声的影响,这会影响雷达图像的解释。因此,图像增强是提高SAR图像清晰度的重要课题。提出了一种基于非下采样轮廓波变换(NSCT)的非线性图像增强算法。通过非下采样轮廓波变换将图像分解为不同比例和方向的系数。它通过NSCT系数的多尺度乘积的阈值方法去噪。然后根据每个尺度的系数确定非线性增强函数的阈值。通过求解非线性方程,可以得到该函数的两个参数,其中一个用于控制增强的范围,另一个可以确定增强的强度。由增强函数处理的系数用于重建图像。在Matlab平台上的仿真结果表明,该算法在增强图像细节和抑制噪声信号方面具有良好的效果。

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