Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update sta...Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update stages of the lifting morphological operator is adopted for preserving local maxima of a signal over several scales,which is particularly useful in wavelet\|based signal detec tion.The new transform presented in the paper is applied in multiresoluti on edge detection of medical image and experim ent results are given to show better performance and applicable potentiali ty.展开更多
The paper presents a fast algorithm for image retrieval using multi-channel textural features in medical picture archiving and communication system （PACS）. By choosing different linear or nonlinear operators in pred...The paper presents a fast algorithm for image retrieval using multi-channel textural features in medical picture archiving and communication system （PACS）. By choosing different linear or nonlinear operators in prediction and update lifting step, the linear or nonlinear M-band wavelet decomposition can be achieved in M-band lifting. It provides the advantages such as fast transform, in-place calculation and integer-integer transform. The set of wavelet moment forms multi-channel textural feature vector related to the texture distribution of each wavelet images. The experimental results of CT image database show that the retrieval approach of multi-channel textural features is effective for image indexing and has lower computational complexity and less memory. It is much easier to implement in hardware and suitable for the applications of real time medical processing system.展开更多
基金Supported by the National Natural Science Foundation dation of China(69983005)
文摘Lifting scheme is a useful and very general technique for constructing wavelet decomposition.The paper adapts the lifting into redundant lifting to obtain shift invariant wavelet transform.In prediction and update stages of the lifting morphological operator is adopted for preserving local maxima of a signal over several scales,which is particularly useful in wavelet\|based signal detec tion.The new transform presented in the paper is applied in multiresoluti on edge detection of medical image and experim ent results are given to show better performance and applicable potentiali ty.
文摘The paper presents a fast algorithm for image retrieval using multi-channel textural features in medical picture archiving and communication system （PACS）. By choosing different linear or nonlinear operators in prediction and update lifting step, the linear or nonlinear M-band wavelet decomposition can be achieved in M-band lifting. It provides the advantages such as fast transform, in-place calculation and integer-integer transform. The set of wavelet moment forms multi-channel textural feature vector related to the texture distribution of each wavelet images. The experimental results of CT image database show that the retrieval approach of multi-channel textural features is effective for image indexing and has lower computational complexity and less memory. It is much easier to implement in hardware and suitable for the applications of real time medical processing system.
