A selective subband enhancement method based on biorthogonal wavelet base is proposed. This novel image enhancement method is just for those images in which the energy of target information area is relatively lower. I...A selective subband enhancement method based on biorthogonal wavelet base is proposed. This novel image enhancement method is just for those images in which the energy of target information area is relatively lower. It includes two parts: one is enhancing the low frequency subband by wavelet decomposition and the other is building a new criterion based on entropy window to image evaluation. Experimental results show that this new scheme may result in a perfect image processing.展开更多
For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background mod...For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.展开更多
基金Project (2003AA1Z2610) supported by National High Technology Research and Development Programof China
文摘A selective subband enhancement method based on biorthogonal wavelet base is proposed. This novel image enhancement method is just for those images in which the energy of target information area is relatively lower. It includes two parts: one is enhancing the low frequency subband by wavelet decomposition and the other is building a new criterion based on entropy window to image evaluation. Experimental results show that this new scheme may result in a perfect image processing.
基金Project(60772080) supported by the National Natural Science Foundation of ChinaProject(3240120) supported by Tianjin Subway Safety System, Honeywell Limited, China
文摘For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.
