diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 515a7990306b6..c847b82e01641 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -10,12 +10,13 @@
 # License: BSD 3 clause
 
 from itertools import product
-import numbers
+from numbers import Integral, Number, Real
 import numpy as np
 from scipy import sparse
 from numpy.lib.stride_tricks import as_strided
 
 from ..utils import check_array, check_random_state
+from ..utils._param_validation import Interval
 from ..base import BaseEstimator
 
 __all__ = [
@@ -249,11 +250,11 @@ def _compute_n_patches(i_h, i_w, p_h, p_w, max_patches=None):
     all_patches = n_h * n_w
 
     if max_patches:
-        if isinstance(max_patches, (numbers.Integral)) and max_patches < all_patches:
+        if isinstance(max_patches, (Integral)) and max_patches < all_patches:
             return max_patches
-        elif isinstance(max_patches, (numbers.Integral)) and max_patches >= all_patches:
+        elif isinstance(max_patches, (Integral)) and max_patches >= all_patches:
             return all_patches
-        elif isinstance(max_patches, (numbers.Real)) and 0 < max_patches < 1:
+        elif isinstance(max_patches, (Real)) and 0 < max_patches < 1:
             return int(max_patches * all_patches)
         else:
             raise ValueError("Invalid value for max_patches: %r" % max_patches)
@@ -299,9 +300,9 @@ def _extract_patches(arr, patch_shape=8, extraction_step=1):
 
     arr_ndim = arr.ndim
 
-    if isinstance(patch_shape, numbers.Number):
+    if isinstance(patch_shape, Number):
         patch_shape = tuple([patch_shape] * arr_ndim)
-    if isinstance(extraction_step, numbers.Number):
+    if isinstance(extraction_step, Number):
         extraction_step = tuple([extraction_step] * arr_ndim)
 
     patch_strides = arr.strides
@@ -502,6 +503,16 @@ class PatchExtractor(BaseEstimator):
     Patches shape: (545706, 2, 2)
     """
 
+    _parameter_constraints: dict = {
+        "patch_size": [tuple, None],
+        "max_patches": [
+            None,
+            Interval(Real, 0, 1, closed="neither"),
+            Interval(Integral, 1, None, closed="left"),
+        ],
+        "random_state": ["random_state"],
+    }
+
     def __init__(self, *, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size
         self.max_patches = max_patches
@@ -526,6 +537,7 @@ def fit(self, X, y=None):
         self : object
             Returns the instance itself.
         """
+        self._validate_params()
         return self
 
     def transform(self, X):
diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
index bb65d30731bf6..abd91efbf1ad7 100644
--- a/sklearn/tests/test_common.py
+++ b/sklearn/tests/test_common.py
@@ -473,7 +473,6 @@ def test_estimators_do_not_raise_errors_in_init_or_set_params(Estimator):
     "OPTICS",
     "OneVsOneClassifier",
     "OneVsRestClassifier",
-    "PatchExtractor",
     "RANSACRegressor",
     "RidgeCV",
     "RidgeClassifierCV",