diff --git a/basic/views.py b/basic/views.py
index 5a0da96..75f30f4 100644
--- a/basic/views.py
+++ b/basic/views.py
@@ -906,6 +906,65 @@ def process_harmonic_filter(img):
     return output
 
 
+def get_middle(array):
+    # 列表的长度
+    length = len(array)
+    # 对列表进行选择排序，获得有序的列表
+    for i in range(length):
+        for j in range(i + 1, length):
+            # 选择最大的值
+            if array[j] > array[i]:
+                # 交换位置
+                temp = array[j]
+                array[j] = array[i]
+                array[i] = temp
+    return array[int(length / 2)]
+
+
+def process_max_sort(img):
+    output = np.zeros(img.shape, np.uint8)
+    array = []
+    for i in range(img.shape[0]):
+        for j in range(img.shape[1]):
+            array.clear()
+            for m in range(-1, 2):
+                for n in range(-1, 2):
+                    if 0 <= i + m < img.shape[0] and 0 <= j + n < img.shape[1]:
+                        array.append(img[i + m][j + n])
+            array.sort(reverse=True)
+            output[i][j] = max(array[0], img[i][j])
+    return output
+
+
+def process_min_sort(img):
+    output = np.zeros(img.shape, np.uint8)
+    array = []
+    for i in range(img.shape[0]):
+        for j in range(img.shape[1]):
+            array.clear()
+            for m in range(-1, 2):
+                for n in range(-1, 2):
+                    if 0 <= i + m < img.shape[0] and 0 <= j + n < img.shape[1]:
+                        array.append(img[i + m][j + n])
+            array.sort()
+            output[i][j] = min(array[0], img[i][j])
+    return output
+
+
+def process_median_sort(img):
+    output = np.zeros(img.shape, np.uint8)
+    array = []
+    for i in range(img.shape[0]):
+        for j in range(img.shape[1]):
+            array.clear()
+            for m in range(-1, 2):
+                for n in range(-1, 2):
+                    if 0 <= i + m < img.shape[0] and 0 <= j + n < img.shape[1]:
+                        array.append(img[i + m][j + n])
+            output[i][j] = get_middle(array)
+    return output
+
+
 @csrf_exempt
 def filtration(request):
     if request.method == 'POST':
@@ -913,14 +972,21 @@ def filtration(request):
         image = para['img']
         img = cv2.imread(PREFIX + image, 0)
         op = para['type']
+        detail_type = para['detail_type']
         if op == 'mean':
-            mean_type = para['mean_type']
-            if mean_type == 'arithmetic':
+            if detail_type == 'arithmetic':
                 img = process_arithmetic_mean(img)
-            elif mean_type == 'geometric':
+            elif detail_type == 'geometric':
                 img = process_geometric_mean(img)
-            elif mean_type == 'harmonic':
+            elif detail_type == 'harmonic':
                 img = process_harmonic_filter(img)
+        elif op == 'sort':
+            if detail_type == 'max':
+                img = process_max_sort(img)
+            elif detail_type == 'median':
+                img = process_median_sort(img)
+            elif detail_type == 'min':
+                img = process_min_sort(img)
         filename = getImageName() + DEFAULT_FORMAT
         cv2.imwrite(PREFIX + filename, img)
         return HttpResponse(filename)