数字图像均值滤波
- 滤波的作用：
对数字图像进行滤波其主要目的是消除其中的噪声，保留图像中的有用信息平滑图像，因此图像滤波也叫图像平滑。图像和数字信号也有共同之处，就是有用信息基本都在低频段或者中频段，这也是信号滤波的基础。
2、均值滤波原理：
均值滤波过程中，使用周围像素点的均值来代替中心点的值。其数学解释在于，当某一个点的远低于或者远大于其他像素点的值时，使用均值代替该点的值可以使得该点更接近于真实值。
3、代码
def Mean_Filter(self, padding = None):
imgarray = self.Add_Salt_Noise()
height, width = imgarray.shape[0], imgarray.shape[1]
if not padding:
edge = int((self.k -1)/2)
if height -1 -edge <=edge or width -1-edge<=edge:
print("the kenerl is to long")
return None
for i in range(height):
for j in range(width):
if i <=edge -1 or i >= height -1 -edge or j <=edge -1 or j >= height -1 -edge:
imgarray[i][j] = imgarray[i][j]
else:
num = []
sum0 = 0
sum1 = 0
sum2 = 0
for m in range(i - edge, i + edge + 1):
for n in range(j -edge, j+edge + 1):
sum0 = sum0 + imgarray[m][n][0]
sum1 = sum1 + imgarray[m][n][1]
sum2 = sum2 + imgarray[m][n][2]
mean0 = sum0 / (self.k * self.k)
mean1 = sum1 / (self.k * self.k)
mean2 = sum2 / (self.k * self.k)
mean =[mean0, mean1, mean2]
print("mean", mean)
imgarray[i][j] = mean #赋值
new_img = Image.fromarray(imgarray)
new_img.save(self.mean_img)
def Add_Salt_Noise(self): # 加椒盐噪声
img = Image.open(self.source_img)
imgarray = np.array(img)
height,width = imgarray.shape[0], imgarray.shape[1]
for i in range(height):
for j in range(width):
if np.random.random(1) < 0.05:
if np.random.random(1) < 0.3:
imgarray[i][j] = 0
else:
imgarray[i][j] = 255
new_img = Image.fromarray(imgarray)
new_img.save(self.noise_img)
return imgarray