图像的离散小波分解（不同种类噪声，Python）

摘要：import matplotlib.image as mpimgimport matplotlib.pyplot as pltimport numpy as npimport sysimport osimport cv2from skimage.util im

import matplotlib.image as mpimgimport matplotlib.pyplot as pltimport numpy as npimport sysimport osimport cv2from skimage.util import random_noisesys.path.append('../')from Wavelet_2D import Wavelet_2DSAVE_OUNTPUTS = Falseif SAVE_OUNTPUTS:OUTPUT_DIR = './Outputs'OUTPUT_FORMAT = '.pdf'if not os.path.isdir(OUTPUT_DIR):os.mkdir(OUTPUT_DIR)plt.rc('text', usetex=True)plt.rc('font', family='serif')image = mpimg.imread('IMG_20210109_014553_621.png')image = image[:, :, :3]if image.dtype != np.uint8:tmp1 = np.zeros_like(image, dtype=np.uint8)for j in range(3):tmp1[:, :, j] = 255 * (image[:, :, j] - np.min(image[:, :, j])) / (np.max(image[:, :, j]) - np.min(image[:, :, j]))image = tmp1image = cv2.resize(image, (256, 256))image_sp = 255*random_noise(image, mode='s&p', amount=0.1)image_gs = 255*random_noise(image, mode='gaussian', mean=0, var=0.05)plt.figure(figsize=(10,5))plt.subplot(1, 3, 1)plt.imshow(image)plt.title('Original Image', fontsize=15)plt.xticks(); plt.yticks()plt.subplot(1, 3, 2)plt.imshow(image_sp.astype(np.uint8))plt.title('Salt\&Pepper Noise', fontsize=15)plt.xticks(); plt.yticks()plt.subplot(1, 3, 3)plt.imshow(image_gs.astype(np.uint8))plt.title('Gaussian Noise', fontsize=15)plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Image'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

SS_haar, SD_haar, DS_haar, DD_haar = Wavelet_2D(image,'Haar', 5)SS_haar_sp, SD_haar_sp, DS_haar_sp, DD_haar_sp = Wavelet_2D(image_sp,'Haar', 5)SS_haar_gs, SD_haar_gs, DS_haar_gs, DD_haar_gs = Wavelet_2D(image_gs,'Haar', 5)Processing Haar Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Haar Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Haar Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!SS_db4, SD_db4, DS_db4, DD_db4 = Wavelet_2D(image,'db4', 5)SS_db4_sp, SD_db4_sp, DS_db4_sp, DD_db4_sp = Wavelet_2D(image_sp,'db4', 5)SS_db4_gs, SD_db4_gs, DS_db4_gs, DD_db4_gs = Wavelet_2D(image_gs,'db4', 5)Processing Daubechies4 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Daubechies4 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Daubechies4 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!SS_db6, SD_db6, DS_db6, DD_db6 = Wavelet_2D(image,'db6', 5)SS_db6_sp, SD_db6_sp, DS_db6_sp, DD_db6_sp = Wavelet_2D(image_sp,'db6', 5)SS_db6_gs, SD_db6_gs, DS_db6_gs, DD_db6_gs = Wavelet_2D(image_gs,'db6', 5)Processing Daubechies6 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Daubechies6 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Daubechies6 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!SS_mh, SD_mh, DS_mh, DD_mh = Wavelet_2D(image,'mexicanHat', 5)SS_mh_sp, SD_mh_sp, DS_mh_sp, DD_mh_sp = Wavelet_2D(image_sp,'mexicanhat', 5)SS_mh_gs, SD_mh_gs, DS_mh_gs, DD_mh_gs = Wavelet_2D(image_gs,'mexicanhat', 5)Processing Mexican Hat Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Mexican Hat Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Mexican Hat Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!SS_sym2, SD_sym2, DS_sym2, DD_sym2 = Wavelet_2D(image,'sym2', 5)SS_sym2_sp, SD_sym2_sp, DS_sym2_sp, DD_sym2_sp = Wavelet_2D(image_sp,'sym2', 5)SS_sym2_gs, SD_sym2_gs, DS_sym2_gs, DD_sym2_gs = Wavelet_2D(image_gs,'sym2', 5)Processing Symlet2 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Symlet2 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!Processing Symlet2 Wavelet Decomposition ...Decomposition Level 1 Completed!Decomposition Level 2 Completed!Decomposition Level 3 Completed!Decomposition Level 4 Completed!Decomposition Level 5 Completed!import matplotlib.pyplot as pltplt.rc('text', usetex=True)plt.rc('font', family='serif')plt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image)plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Haar Wavelet - Image Without Noise', fontsize=20)for i in range(len(SS_haar)):tmp1 = SS_haar[i].astype(np.uint8)tmp2 = SD_haar[i].astype(np.uint8)tmp3 = DS_haar[i].astype(np.uint8)tmp4 = DD_haar[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_HaarWavelet_WithoutNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_sp.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Haar Wavelet - Image With S\&P Noise', fontsize=20)for i in range(len(SS_haar_sp)):tmp1 = SS_haar_sp[i].astype(np.uint8)tmp2 = SD_haar_sp[i].astype(np.uint8)tmp3 = DS_haar_sp[i].astype(np.uint8)tmp4 = DD_haar_sp[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_HaarWavelet_SPNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_gs.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Haar Wavelet - Image With Gaussian Noise', fontsize=20)for i in range(len(SS_haar_gs)):tmp1 = SS_haar_gs[i].astype(np.uint8)tmp2 = SD_haar_gs[i].astype(np.uint8)tmp3 = DS_haar_gs[i].astype(np.uint8)tmp4 = DD_haar_gs[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_HaarWavelet_GaussianNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

import matplotlib.pyplot as pltplt.rc('text', usetex=True)plt.rc('font', family='serif')plt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image)plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies4 Wavelet - Image Without Noise', fontsize=20)for i in range(len(SS_db4)):tmp1 = SS_db4[i].astype(np.uint8)tmp2 = SD_db4[i].astype(np.uint8)tmp3 = DS_db4[i].astype(np.uint8)tmp4 = DD_db4[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies4Wavelet_WithoutNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_sp.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies4 Wavelet - Image With S\&P Noise', fontsize=20)for i in range(len(SS_db4_sp)):tmp1 = SS_db4_sp[i].astype(np.uint8)tmp2 = SD_db4_sp[i].astype(np.uint8)tmp3 = DS_db4_sp[i].astype(np.uint8)tmp4 = DD_db4_sp[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies4Wavelet_SPNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_gs.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies4 Wavelet - Image With Gaussian Noise', fontsize=20)for i in range(len(SS_db4_gs)):tmp1 = SS_db4_gs[i].astype(np.uint8)tmp2 = SD_db4_gs[i].astype(np.uint8)tmp3 = DS_db4_gs[i].astype(np.uint8)tmp4 = DD_db4_gs[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies4Wavelet_GaussianNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

import matplotlib.pyplot as pltplt.rc('text', usetex=True)plt.rc('font', family='serif')plt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image)plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies6 Wavelet - Image Without Noise', fontsize=20)for i in range(len(SS_db6)):tmp1 = SS_db6[i].astype(np.uint8)tmp2 = SD_db6[i].astype(np.uint8)tmp3 = DS_db6[i].astype(np.uint8)tmp4 = DD_db6[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies6Wavelet_WithoutNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_sp.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies6 Wavelet - Image With S\&P Noise', fontsize=20)for i in range(len(SS_db6_sp)):tmp1 = SS_db6_sp[i].astype(np.uint8)tmp2 = SD_db6_sp[i].astype(np.uint8)tmp3 = DS_db6_sp[i].astype(np.uint8)tmp4 = DD_db6_sp[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies6Wavelet_SPNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_gs.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Daubechies6 Wavelet - Image With Gaussian Noise', fontsize=20)for i in range(len(SS_db6_gs)):tmp1 = SS_db6_gs[i].astype(np.uint8)tmp2 = SD_db6_gs[i].astype(np.uint8)tmp3 = DS_db6_gs[i].astype(np.uint8)tmp4 = DD_db6_gs[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Daubechies6Wavelet_GaussianNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

import matplotlib.pyplot as pltplt.rc('text', usetex=True)plt.rc('font', family='serif')plt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image)plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Mexican Hat Wavelet - Image Without Noise', fontsize=20)for i in range(len(SS_mh)):tmp1 = SS_mh[i].astype(np.uint8)tmp2 = SD_mh[i].astype(np.uint8)tmp3 = DS_mh[i].astype(np.uint8)tmp4 = DD_mh[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_MexicanHatWavelet_WithoutNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_sp.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Mexican Hat Wavelet - Image With S\&P Noise', fontsize=20)for i in range(len(SS_mh_sp)):tmp1 = SS_mh_sp[i].astype(np.uint8)tmp2 = SD_mh_sp[i].astype(np.uint8)tmp3 = DS_mh_sp[i].astype(np.uint8)tmp4 = DD_mh_sp[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_MexicanHatWavelet_SPNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_gs.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Mexican Hat Wavelet - Image With Gaussian Noise', fontsize=20)for i in range(len(SS_mh_gs)):tmp1 = SS_mh_gs[i].astype(np.uint8)tmp2 = SD_mh_gs[i].astype(np.uint8)tmp3 = DS_mh_gs[i].astype(np.uint8)tmp4 = DD_mh_gs[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_MexicanHatWavelet_GaussianNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

import matplotlib.pyplot as pltplt.rc('text', usetex=True)plt.rc('font', family='serif')plt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image)plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Symlet2 Wavelet - Image Without Noise', fontsize=20)for i in range(len(SS_sym2)):tmp1 = SS_sym2[i].astype(np.uint8)tmp2 = SD_sym2[i].astype(np.uint8)tmp3 = DS_sym2[i].astype(np.uint8)tmp4 = DD_sym2[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Symlet2Wavelet_WithoutNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_sp.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Symlet2 Wavelet - Image With S\&P Noise', fontsize=20)for i in range(len(SS_sym2_sp)):tmp1 = SS_sym2_sp[i].astype(np.uint8)tmp2 = SD_sym2_sp[i].astype(np.uint8)tmp3 = DS_sym2_sp[i].astype(np.uint8)tmp4 = DD_sym2_sp[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Symlet2Wavelet_SPNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.showplt.figure(figsize=(12, 8))plt.subplot(2, 3, 1)plt.imshow(image_gs.astype(np.uint8))plt.title('Input')plt.xticks(); plt.yticks()plt.suptitle('Symlet2 - Image With Gaussian Noise', fontsize=20)for i in range(len(SS_sym2_gs)):tmp1 = SS_sym2_gs[i].astype(np.uint8)tmp2 = SD_sym2_gs[i].astype(np.uint8)tmp3 = DS_sym2_gs[i].astype(np.uint8)tmp4 = DD_sym2_gs[i].astype(np.uint8)tmp11 = np.vstack((tmp1, tmp2))tmp22 = np.vstack((tmp3, tmp4))tmp = np.hstack((tmp11, tmp22))plt.subplot(2, 3, i+2)plt.title(f'Decomposition Level: {i+1}')plt.imshow(tmp.astype(np.uint8))plt.xticks(); plt.yticks()plt.tight_layoutif SAVE_OUNTPUTS:plt.savefig(OUTPUT_DIR+'/2D_Symlet2Wavelet_GaussianNoise'+OUTPUT_FORMAT, bbox_inches='tight')plt.show

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担任《Mechanical System and Signal Processing》《中国电机工程学报》等期刊审稿专家，擅长领域：信号滤波/降噪，机器学习/深度学习，时间序列预分析/预测，设备故障诊断/缺陷检测/异常检测。

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