diff --git a/skimage/restoration/_denoise.py b/skimage/restoration/_denoise.py
index a853a63c..795d3602 100644
--- a/skimage/restoration/_denoise.py
+++ b/skimage/restoration/_denoise.py
@@ -394,7 +394,7 @@ def _wavelet_threshold(img, wavelet, threshold=None, sigma=None, mode='soft'):
     return pywt.waverecn(denoised_coeffs, wavelet)
 
 
-def denoise_wavelet(img, sigma=None, wavelet='db1', mode='soft'):
+def denoise_wavelet(img, multichannel, sigma=None, wavelet='db1', mode='soft'):
     """Performs wavelet denoising on an image.
 
     Parameters
@@ -457,16 +457,13 @@ def denoise_wavelet(img, sigma=None, wavelet='db1', mode='soft'):
 
     img = img_as_float(img)
 
-    if img.ndim not in {2, 3}:
-        raise ValueError('denoise_wavelet only supports 2D and 3D images')
-
-    if img.ndim == 2:
+    if multichannel:
+        out = np.stack([_wavelet_threshold(img[..., c], wavelet=wavelet,
+                                           mode=mode, sigma=sigma)
+                        for c in range(img.ndim)], axis=-1)
+    else:
         out = _wavelet_threshold(img, wavelet=wavelet, mode=mode,
                                  sigma=sigma)
-    else:
-        out = np.dstack([_wavelet_threshold(img[..., c], wavelet=wavelet,
-                                            mode=mode, sigma=sigma)
-                         for c in range(img.ndim)])
 
     clip_range = (-1, 1) if img.min() < 0 else (0, 1)
     return np.clip(out, *clip_range)