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1/1.py

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+from matplotlib import pyplot as plt
+from PIL import Image
+
+plt.rcParams["font.sans-serif"] = ["SimSun"]
+
+pil_im = Image.open("images/house.jpg")
+pil_im1 = Image.open("images/house.jpg").convert("L")
+
+plt.figure()
+plt.subplot(121)
+plt.title("原图")
+plt.axis("off")
+plt.imshow(pil_im)
+plt.subplot(122)
+plt.title("灰度图")
+plt.axis("off")
+plt.imshow(pil_im1, cmap="gray")
+plt.show()

1/2.py

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+from PIL import Image
+
+
+def IsValidImage(img_path):
+    bValid = True
+    try:
+        Image.open(img_path).verify()
+    except:
+        bValid = False
+    return bValid
+
+
+def transimg(img_path):
+    if IsValidImage(img_path):
+        try:
+            str = img_path.rsplit(".", 1)
+            output_img_path = str[0] + ".jpg"
+            print(output_img_path)
+            im = Image.open(img_path)
+            im.save(output_img_path)
+            return True
+        except:
+            return False
+
+
+if __name__ == "__main__":
+    img_path = "images/lena.png"
+    print(transimg(img_path))

1/3.py

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+import numpy as np
+from matplotlib import pyplot as plt
+from PIL import Image
+
+im = np.array(Image.open("images/house.jpg").convert("L"))
+im2 = 255 - im
+print("对图像进行反向处理:\n", int(im.min()), int(im.max()))
+im3 = (100.0 / 255) * im + 100
+print("将图像像素值变换到100...200区间:\n", int(im3.min()), int(im3.max()))
+im4 = 255.0 * (im / 255.0) ** 2
+print("对像素值求平方后得到的图像:\n", int(im4.min()), int(im4.max()))
+
+plt.figure()
+plt.gray()
+plt.subplot(131)
+plt.title("f(x) = 255 - x")
+plt.imshow(im2)
+plt.axis("off")
+plt.subplot(132)
+plt.title("f(x) = 100 / 255 * x + 100")
+plt.imshow(im3)
+plt.axis("off")
+plt.subplot(133)
+plt.title("f(x) = 255 * (x / 255) ^ 2")
+plt.imshow(im4)
+plt.axis("off")
+plt.show()

1/4.py

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+import numpy as np
+from matplotlib import pyplot as plt
+from matplotlib.font_manager import FontProperties
+from PIL import Image
+from scipy.ndimage import filters
+
+plt.rcParams["font.sans-serif"] = ["SimSun"]
+im = np.array(Image.open("images/house.jpg").convert("L"))
+
+plt.figure()
+plt.gray()
+plt.subplot(141)
+plt.title("原图")
+plt.axis("off")
+plt.imshow(im, cmap="gray")
+for bi, blur in enumerate([2, 4, 8]):
+    im2 = np.zeros(im.shape)
+    im2 = filters.gaussian_filter(im, blur)  # type: ignore
+    im2 = np.uint8(im2)
+    imNum = str(blur)
+    plt.subplot(1, 4, 2 + bi)
+    plt.axis("off")
+    plt.title("标准差为 " + imNum)
+    plt.imshow(im2)
+plt.show()

1/5.py

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+import numpy as np
+from matplotlib import pyplot as plt
+from scipy.ndimage import filters
+from skimage.restoration import denoise_tv_chambolle
+
+# import PCV.tools as rof
+
+plt.rcParams["font.sans-serif"] = ["SimSun"]
+im = np.zeros((500, 500))
+im[100:400, 100:400] = 128
+im[200:300, 200:300] = 255
+im = im + 30 * np.random.standard_normal((500, 500))
+U = denoise_tv_chambolle(im, weight=0.1)
+# U, T = rof.denoise(im, im)
+G = filters.gaussian_filter(im, 10)  # type: ignore
+
+plt.figure()
+plt.gray()
+plt.subplot(131)
+plt.title("原噪声图像")
+plt.axis("off")
+plt.imshow(im)
+plt.subplot(132)
+plt.title("高斯模糊后的图像")
+plt.axis("off")
+plt.imshow(G)
+plt.subplot(133)
+plt.title("ROF 降噪后的图像")
+plt.axis("off")
+plt.imshow(U)
+plt.show()