diff --git a/modules/processing_correction.py b/modules/processing_correction.py
index ff038c024..2f842a596 100644
--- a/modules/processing_correction.py
+++ b/modules/processing_correction.py
@@ -29,29 +29,25 @@ def soft_clamp_tensor(tensor, threshold=0.8, boundary=4):
     return tensor
 
 
-def center_tensor(tensor, channel_shift=1.0, full_shift=1.0, channels=[0, 1, 2, 3]): # pylint: disable=dangerous-default-value # noqa: B006
+def center_tensor(tensor, channel_shift=1.0, full_shift=1.0):
     if channel_shift == 0 and full_shift == 0:
         return tensor
-    means = []
-    for channel in channels:
-        means.append(tensor[0, channel].mean())
-        # tensor[0, channel] -= means[-1] * channel_shift
-        tensor[channel] -= means[-1] * channel_shift
-    tensor = tensor - tensor.mean() * full_shift
-    debug(f'HDR center: channel-shift={channel_shift} full-shift={full_shift} means={torch.stack(means)} shape={tensor.shape}')
+    tensor -= tensor.mean(dim=(-1, -2), keepdim=True) * channel_shift
+    tensor -= tensor.mean() * full_shift
+    debug(f'HDR center: channel-shift={channel_shift} full-shift={full_shift}')
+    debug(f'HDR center: After Adjustment: Full mean={tensor.mean().item()} Channel means={tensor.mean(dim=(-1, -2)).cpu().numpy()}')
     return tensor
 
 
-def maximize_tensor(tensor, boundary=1.0, _channels=[0, 1, 2]): # pylint: disable=dangerous-default-value # noqa: B006
+def maximize_tensor(tensor, boundary=1.0):
     if boundary == 1.0:
         return tensor
     boundary *= 4
     min_val = tensor.min()
     max_val = tensor.max()
     normalization_factor = boundary / max(abs(min_val), abs(max_val))
-    # tensor[0, channels] *= normalization_factor
     tensor *= normalization_factor
-    debug(f'HDR maximize: boundary={boundary} min={min_val} max={max_val} factor={normalization_factor} shape={tensor.shape}')
+    debug(f'HDR maximize: boundary={boundary} min={min_val} max={max_val} factor={normalization_factor}')
     return tensor
 
 
@@ -62,7 +58,7 @@ def correction(p, timestep, latent):
     if timestep > 700 and p.hdr_center:
         p.extra_generation_params["HDR center"] = f'{p.hdr_channel_shift}/{p.hdr_full_shift}'
         latent = center_tensor(latent, channel_shift=p.hdr_channel_shift, full_shift=p.hdr_full_shift)
-    if timestep > 1 and timestep < 100 and p.hdr_maximize:
+    if 1 < timestep < 100 and p.hdr_maximize:
         p.extra_generation_params["HDR max"] = f'{p.hdr_max_center}/{p.hdr_max_boundry}'
         latent = center_tensor(latent, channel_shift=p.hdr_max_center, full_shift=1.0)
         latent = maximize_tensor(latent, boundary=p.hdr_max_boundry)
@@ -73,10 +69,16 @@ def correction_callback(p, timestep, kwargs):
     if not p.hdr_clamp and not p.hdr_center and not p.hdr_maximize:
         return kwargs
     latents = kwargs["latents"]
+    debug('')
+    debug(f' Timestep: {timestep}')
     # debug(f'HDR correction: latents={latents.shape}')
     if len(latents.shape) == 4: # standard batched latent
         for i in range(latents.shape[0]):
             latents[i] = correction(p, timestep, latents[i])
+            debug(f"Full Mean: {latents[i].mean().item()}")
+            debug(f"Channel Means: {latents[i].mean(dim=(-1, -2), keepdim=True).flatten().cpu().numpy()}")
+            debug(f"Channel Mins: {latents[i].min(-1, keepdim=True)[0].min(-2, keepdim=True)[0].flatten().cpu().numpy()}")
+            debug(f"Channel Maxes: {latents[i].max(-1, keepdim=True)[0].min(-2, keepdim=True)[0].flatten().cpu().numpy()}")
     elif len(latents.shape) == 5 and latents.shape[0] == 1: # probably animatediff
         latents = latents.squeeze(0).permute(1, 0, 2, 3)
         for i in range(latents.shape[0]):