外文翻译小波变换在图像处理中仿真及应用.docxVIP

附录B Wavelet transform in image processing in simulation and Application 1, task significance In the traditional analysis of signal in frequency domain, is completely unfolded, does not contain any time frequency information, which for some applications it is appropriate, because the frequency of the signal to its information is very important. But its discarded time information may be possible for some applications also is very important, so the analysis of the promotion, put forward a lot of time domain and frequency domain information signal analysis methods, such as short Fourier transform, Gabor transform, time-frequency analysis, wavelet transform. Wavelet analysis overcomes the STFT in a single resolution on the defect, has the characteristics of multi-resolution analysis, which has been widely applied in image processing. The traditional signal theory, is built on the basis of the analysis of Fourier, Fourier transform is a kind of global change, it has some limitations. In practical application, the people start to Fourier transform are improved, thus resulting in wavelet analysis. Wavelet analysis is a new branch of mathematics, it is a universal function, Fourier analysis, harmonic analysis, numerical analysis of the most perfect crystalline; in the fields of application, especially in signal processing, image processing, speech processing and nonlinear science domain, it is considered to be the Fourier analysis after another effective when frequency analysis method. Wavelet transform and Fourier transform, is a time and frequency domain of the local transform which can effectively extracted from the signal information, through dilation and shift operation function to function or signal multiscale analysis ( Multiscale Analysis ), to solve the Fourier transform can not solve many difficult problems Wavelet transform is a rapid development and more popular signal analysis method, the image processing is a very important application, including image compress