In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field...In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field-programmable gate array(FPGA),which uses a 3-level pipeline paralleled 5/3 lifting wavelet transformation and reconstruction structure,as well as a fast BayesS hrink adaptive threshold filtering module.The proposed system demonstrates de-noising performance,while also balancing system resources and achieving real-time processing.The experiments show that the proposed system's maximum operating frequency(through logic synthesis and layout using Quartus 13.1 software) can reach 178 MHz,based on the Altera Company's Stratix III EP3SE80 series FPGA.The proposed system can also satisfy real-time de-noising requirements of 1920 × 1080 at60 fps HD-video sources,while also significantly improving the peak signal to noise rate of the denoising images.Compared with similar systems,the system has the advantages of high operating frequency,and the ability to support multiple source formats for real-time processing.展开更多
A novel image denoising method is proposed based on multiscale wavelet thresholding （WT） and bilateral filtering （BF）. First, the image is decomposed into multiscale subbands by wavelet transform. Then, from the t...A novel image denoising method is proposed based on multiscale wavelet thresholding （WT） and bilateral filtering （BF）. First, the image is decomposed into multiscale subbands by wavelet transform. Then, from the top scale to the bottom scale, we apply BF to the approximation subbands and WT to the detail subbands. The filtered subbands are reconstructed back to ap- proximation subbands of the lower scale. Finally, subbands are reconstructed in all the scales, and in this way the denoised image is formed. Different from conventional methods such as WT and BF, it can smooth the low-frequency noise efficiently. Experiment results on the image Lena and Rice show that the peak sig- nal-to-noise ratio （PSNR） is improved by at least 3 dB and 0.7 dB compared with using the WT and BF, respectively. In addition, the computational time of the proposed method is almost comparable with that of WT but much less than that of BF.展开更多
基金Supported by the Spark Program of China(No.2013GA780007)Key Scientific Research Project of Guandong Agriculture Industry Business Polytechnic(No.xyzd1604)
文摘In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field-programmable gate array(FPGA),which uses a 3-level pipeline paralleled 5/3 lifting wavelet transformation and reconstruction structure,as well as a fast BayesS hrink adaptive threshold filtering module.The proposed system demonstrates de-noising performance,while also balancing system resources and achieving real-time processing.The experiments show that the proposed system's maximum operating frequency(through logic synthesis and layout using Quartus 13.1 software) can reach 178 MHz,based on the Altera Company's Stratix III EP3SE80 series FPGA.The proposed system can also satisfy real-time de-noising requirements of 1920 × 1080 at60 fps HD-video sources,while also significantly improving the peak signal to noise rate of the denoising images.Compared with similar systems,the system has the advantages of high operating frequency,and the ability to support multiple source formats for real-time processing.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2006AA040307)
文摘A novel image denoising method is proposed based on multiscale wavelet thresholding （WT） and bilateral filtering （BF）. First, the image is decomposed into multiscale subbands by wavelet transform. Then, from the top scale to the bottom scale, we apply BF to the approximation subbands and WT to the detail subbands. The filtered subbands are reconstructed back to ap- proximation subbands of the lower scale. Finally, subbands are reconstructed in all the scales, and in this way the denoised image is formed. Different from conventional methods such as WT and BF, it can smooth the low-frequency noise efficiently. Experiment results on the image Lena and Rice show that the peak sig- nal-to-noise ratio （PSNR） is improved by at least 3 dB and 0.7 dB compared with using the WT and BF, respectively. In addition, the computational time of the proposed method is almost comparable with that of WT but much less than that of BF.
