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基于小波变换的去雾处理程序，附有实验图片，可以运行的，希望对大家有帮助！(Based on wavelet transform to fog handler, attached to the experimental images, you can run, I hope it can help you!)

1.实现非抽样提升小波包三层分解 2.有效解决了小波包分解频带交错问题 3.有效输出频谱图(1 non-sampling improved wavelet packet three decomposition. Effective solution to the wavelet packet decomposition band interlacing problems. Effective output spectrogram)

这是二维离散小波变换程序，里面附带程序说明，及实例讲解。(This is a two-dimensional discrete wavelet transform, which comes with the program instructions and examples to explain.)

小波变换测试，小波分解的级数设置为3级，可以实现数字图像的小波变化和逆变化。测试代码请使用512*512灰度图像(The wavelet transformation test, wavelet decomposition series is set to 3, digital image wavelet changes and reverse changes.)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

一篇很好的小波变换英文入门资料，附有注释，对想了解小波变换的初学者十分有益。(A good wavelet transform introductory information in English, annotated, very useful for beginners want to learn wavelet transform.)

滚动轴承外圈故障频率，小波分析后包络变换，数据来源西储大学

根据采集的时域数据，做fft得到其频谱，并计算其功率谱密度(According to the collected time-domain data, the frequency spectrum is obtained by FFT and the power spectral density is calculated.)

离散小波变换是指在特定子集上采取缩放和平移的小波变换，是一种兼具时域和频域多分辨率能力的信号分析工具。此变换运用可以缩放平移的小波代替固定的窗进行计算分析，主要应用于信号编码和数据压缩。(Discrete wavelet transform refers to the specific subset take scaling and translation on the wavelet transform, is a kind of multi-resolution ability both time domain and frequency domain signal analysis tool. This transformation can use zoom translational wavelet calculation and analysis instead of the fixed window, mainly used in signal coding and data compression. )