filter_data = kf.updata(input_data) print(f"滤波后:filter_data") import numpy as np import matplotlib.pyplot as plt sensor_data = np.random.randn(200) n = 11 filter_sensor_data = np.zeros_like(sensor_data) for i i
首先,我们需要导入numpy和scipy库: importnumpyasnpfromscipy.signalimportfirwin,lfilter 1. 2. 接下来,我们定义一个函数apply_lowpass_filter来应用FIR低通滤波器: defapply_lowpass_filter(signal,cutoff_freq,sampling_freq,filter_order):# 计算滤波器的系数nyquist_freq=0.5*sampling_freq normalized_cutoff_freq=...
(1)以下为低通(高通滤波器类似这样设计)滤波器的一个demo: importnumpyasnpfromscipy.signalimportbutter,filtfiltimportmatplotlib.pyplotaspltdefbutter_lowpass_filter(data,cutoff,fs,order=4):nyq=0.5*fsnormal_cutoff=cutoff/nyqb,a=butter(order,normal_cutoff,btype='low',analog=False)#高通滤波器btype='...
y = np.sin(2*np.pi*f * (x/fs)) # design the lowpass filter nyquist = 0.5 * fs low = f / nyquist b, a = signal.butter(10, low, 'low') # apply the filter to the data y_lowpass = signal.filtfilt(b, a, y) 这是一段带通滤波器的代码,其中使用了Butterworth滤波器设计和 fi...
7.高通滤波(highpass_filter)规则为高频信号能正常通过,而低于设定临界值的低频信号则被阻隔、减弱。但是阻隔、减弱的幅度则会依据不同的频率以及不同的滤波程序(目的)而改变。它有的时候也被叫做低频去除过滤(low-cut filter)。 代码语言:javascript 复制 ...
low_pass_filter[center_row - bandwidth // 2 : center_row + bandwidth // 2, center_col - bandwidth // 2 : center_col + bandwidth // 2] = 1 # 进行滤波 f_transform_shifted_filtered = f_transform_shifted * gauss_filter 过滤完后,在看下频谱 矩形滤波只保留了中心频谱,然后用逆傅立叶变...
plt.imshow(lowPassFilter(img,60),cmap="gray") 高通滤波器 高通滤波器同低通滤波器非常类似,只不过二者通过的波正好是相反的 H(u,v)={0,ifD(u,v)≤D01,ifD(u,v)≥D0H(u,v)={0,ifD(u,v)≤D01,ifD(u,v)≥D0 defhighPassFilter(image,d): ...
plt.title('lowPassFilter') plt.subplot(224) plt.imshow(highPassFilter(img,50),cmap="gray") plt.axis("off") plt.title('highPassFilter') plt.show() 图像噪声与去噪算法 中值滤波 概述: 中值滤波是一种非线性空间滤波器, 它的响应基于图像滤波器包围的图像区域中像素的统计排序, ...
= ax[0, 0].imshow(np.abs(idealFilterLP(50, img.shape)), cmap='gray')ax[0, 0].set_title('Low Pass Filter of Diameter 50 px')ax[0, 0].set_xticks([])ax[0, 0].set_yticks([])# plot the second image in the top-right subplotim2 = ax[0, 1].imshow(np.abs(idealFilterHP...
def butter_lowpass_filter(signal, cutoff, fs, order): b, a = butter_lowpass(cutoff, fs, order) smoothed_signal = lfilter(b, a, signal) return smoothed_signal ``` 其中,cutoff是截止频率,fs是采样率,order是滤波器的阶数。函数中首先使用butter函数设计了低通滤波器,然后使用lfilter函数对输入信号...