Nearfield acoustic holography(NAH)is a powerful tool for realizing source identification and sound field reconstruction.The wave superposition(WS)-based NAH is appropriate for the spatially extended sources and does n...Nearfield acoustic holography(NAH)is a powerful tool for realizing source identification and sound field reconstruction.The wave superposition(WS)-based NAH is appropriate for the spatially extended sources and does not require the complex numerical integrals.Equivalent source method(ESM),as a classical WS approach,is widely used due to its simplicity and efficiency.In the ESM,a virtual source surface is introduced,on which the virtual point sources are taken as the assumed sources,and an optimal retreat distance needs to be considered.A newly proposed WS-based approach,the element radiation superposition method(ERSM),uses piston surface source as the assumed source with no need to choose a virtual source surface.To satisfy the application conditions of piston pressure formula,the sizes of pistons are assumed to be as small as possible,which results in a large number of pistons and sampling points.In this paper,transfer matrix modes(TMMs),which are composed of the singular vectors of the vibro-acoustic transfer matrix,are used as the sparse basis of piston normal velocities.Then,the compressive ERSM based on TMMs is proposed.Compared with the conventional ERSM,the proposed method maintains a good pressure reconstruction when the number of sampling points and pistons are both reduced.Besides,the proposed method is compared with the compressive ESM in a mathematical sense.Both simulations and experiments for a rectangular plate demonstrate the advantage of the proposed method over the existing methods.展开更多
针对雾霾环境下驾驶员对前方环境辨别能力差、处理图像时干扰因素过多等问题,提出了一种基于引导图像滤波和Prewitt算子相结合的方法。本方法通过含有包滤波器的引导图像滤波去除雾霾影响,然后借助霍夫(Hough)变换对道路边缘进行检测以...针对雾霾环境下驾驶员对前方环境辨别能力差、处理图像时干扰因素过多等问题,提出了一种基于引导图像滤波和Prewitt算子相结合的方法。本方法通过含有包滤波器的引导图像滤波去除雾霾影响,然后借助霍夫(Hough)变换对道路边缘进行检测以寻找到感兴趣区域(Regions of Interest,ROI),最后对这一区域的图像使用Prewitt算子的边缘检测进行处理以识别出车辆前方的障碍物。该方法不仅能有效避免驾驶员因视线差而导致的事故,而且提高了障碍物的识别效果。展开更多
基金the financial support provided by the National Natural Science Foundation of China (Nos. 51701114, 11604204, 51805313)the Youth Teacher Development Program of Shanghai Universities, China (No. ZZGCD15101)。
基金Project supported by the National Natural Science Foundation of China(Grant No.61701133)。
文摘Nearfield acoustic holography(NAH)is a powerful tool for realizing source identification and sound field reconstruction.The wave superposition(WS)-based NAH is appropriate for the spatially extended sources and does not require the complex numerical integrals.Equivalent source method(ESM),as a classical WS approach,is widely used due to its simplicity and efficiency.In the ESM,a virtual source surface is introduced,on which the virtual point sources are taken as the assumed sources,and an optimal retreat distance needs to be considered.A newly proposed WS-based approach,the element radiation superposition method(ERSM),uses piston surface source as the assumed source with no need to choose a virtual source surface.To satisfy the application conditions of piston pressure formula,the sizes of pistons are assumed to be as small as possible,which results in a large number of pistons and sampling points.In this paper,transfer matrix modes(TMMs),which are composed of the singular vectors of the vibro-acoustic transfer matrix,are used as the sparse basis of piston normal velocities.Then,the compressive ERSM based on TMMs is proposed.Compared with the conventional ERSM,the proposed method maintains a good pressure reconstruction when the number of sampling points and pistons are both reduced.Besides,the proposed method is compared with the compressive ESM in a mathematical sense.Both simulations and experiments for a rectangular plate demonstrate the advantage of the proposed method over the existing methods.
文摘针对雾霾环境下驾驶员对前方环境辨别能力差、处理图像时干扰因素过多等问题,提出了一种基于引导图像滤波和Prewitt算子相结合的方法。本方法通过含有包滤波器的引导图像滤波去除雾霾影响,然后借助霍夫(Hough)变换对道路边缘进行检测以寻找到感兴趣区域(Regions of Interest,ROI),最后对这一区域的图像使用Prewitt算子的边缘检测进行处理以识别出车辆前方的障碍物。该方法不仅能有效避免驾驶员因视线差而导致的事故,而且提高了障碍物的识别效果。
