探讨了多小波函数及其预处理方法对探地雷达(ground penetrating radar—GPR)图象去噪性能的影响,在Donoho D L和Johnstone I M提出的小波阈值去噪方法的基础上提出了一个改进的阈值函数,并对实际的GPR图象进行阈值化处理和对比分析,结...探讨了多小波函数及其预处理方法对探地雷达(ground penetrating radar—GPR)图象去噪性能的影响,在Donoho D L和Johnstone I M提出的小波阈值去噪方法的基础上提出了一个改进的阈值函数,并对实际的GPR图象进行阈值化处理和对比分析,结果表明选取合适的预处理方法,采用DGHM和STT多小波对GPR图象去噪可获得比其他方法更好的效果。展开更多
In order to solve complex algorithm that is difficult to achieve real-time processing of Multiband image fusion within large amount of data, a real-time image fusion system based on FPGA and multi-DSP is designed. Fiv...In order to solve complex algorithm that is difficult to achieve real-time processing of Multiband image fusion within large amount of data, a real-time image fusion system based on FPGA and multi-DSP is designed. Five-band image acquisition, image registration, image fusion and display output can be done within the system which uses FPGA as the main processor and the other three DSP as an algorithm processor. Making full use of Flexible and high-speed characteristics of FPGA, while an image fusion algorithm based on multi-wavelet transform is optimized and applied to the system. The final experimental results show that the frame rate of 15 Hz, with a resolution of 1392 × 1040 of the five-band image can be used by the system to complete processing within 41ms.展开更多
文摘探讨了多小波函数及其预处理方法对探地雷达(ground penetrating radar—GPR)图象去噪性能的影响,在Donoho D L和Johnstone I M提出的小波阈值去噪方法的基础上提出了一个改进的阈值函数,并对实际的GPR图象进行阈值化处理和对比分析,结果表明选取合适的预处理方法,采用DGHM和STT多小波对GPR图象去噪可获得比其他方法更好的效果。
文摘In order to solve complex algorithm that is difficult to achieve real-time processing of Multiband image fusion within large amount of data, a real-time image fusion system based on FPGA and multi-DSP is designed. Five-band image acquisition, image registration, image fusion and display output can be done within the system which uses FPGA as the main processor and the other three DSP as an algorithm processor. Making full use of Flexible and high-speed characteristics of FPGA, while an image fusion algorithm based on multi-wavelet transform is optimized and applied to the system. The final experimental results show that the frame rate of 15 Hz, with a resolution of 1392 × 1040 of the five-band image can be used by the system to complete processing within 41ms.
