diff --git a/comfy_extras/nodes_chroma_radiance.py b/comfy_extras/nodes_chroma_radiance.py
index 3888dc481..4773fff74 100644
--- a/comfy_extras/nodes_chroma_radiance.py
+++ b/comfy_extras/nodes_chroma_radiance.py
@@ -10,8 +10,8 @@ class EmptyChromaRadianceLatentImage:
 
     @classmethod
     def INPUT_TYPES(s):
-        return {"required": { "width": ("INT", {"default": 1024, "min": 2, "max": nodes.MAX_RESOLUTION}),
-                              "height": ("INT", {"default": 1024, "min": 2, "max": nodes.MAX_RESOLUTION}),
+        return {"required": { "width": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
+                              "height": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
                               "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096})}}
     RETURN_TYPES = ("LATENT",)
     FUNCTION = "go"
@@ -57,6 +57,19 @@ class ChromaRadianceImageToLatent:
     CATEGORY = "latent/chroma_radiance"
 
     def go(self, *, image):
+        if image.ndim == 3:
+            image = image.unsqueeze(0)
+        elif image.ndim != 4:
+            raise ValueError("Unexpected input image shape")
+        h, w, c = image.shape[1:]
+        if h < 16 or w < 16 or not (h / 16).is_integer() or not (w / 16).is_integer():
+            raise ValueError("Chroma Radiance image inputs must have sizes that are multiples of 16.")
+        if c > 3:
+            image = image[..., :3]
+        elif c == 1:
+            image = image.expand(-1, -1, -1, 3)
+        elif c != 3:
+            raise ValueError("Unexpected number of channels in input image")
         latent = image.to(device=self.device, dtype=torch.float32, copy=True)
         latent = latent.clamp_(0, 1).movedim(-1, 1).contiguous()
         latent -= 0.5