diff --git a/jobs/process/BaseSDTrainProcess.py b/jobs/process/BaseSDTrainProcess.py
index e55525aa..01418c74 100644
--- a/jobs/process/BaseSDTrainProcess.py
+++ b/jobs/process/BaseSDTrainProcess.py
@@ -1330,6 +1330,21 @@ class BaseSDTrainProcess(BaseTrainProcess):
                     batch_noise = batch_noise * scn_scale
                     noise = noise + batch_noise 
                 
+                if self.train_config.do_batch_noise_correction:
+                    if latents.shape[0] == 1:
+                        # if we only have a batch size of 1, then we cant do batch noise correction, so we skip it
+                        print_acc("Skipping batch noise correction because batch size is 1, increase batch size and num_repeats to use this feature")
+                    else:
+                        # shuffle tensors ensuring that no tensor is in the same position as before
+                        batch_noise = latents.clone().roll(shifts=torch.randint(1, latents.shape[0], (1,)).item(), dims=0).to(noise.device, dtype=noise.dtype)
+                        batch_noise_scale = torch.randn(
+                            batch_noise.shape[0], batch_noise.shape[1], 1, 1,
+                            device=batch_noise.device,
+                            dtype=batch_noise.dtype
+                        ) * self.train_config.batch_noise_correction_scale
+                        batch_noise = batch_noise * batch_noise_scale
+                        noise = noise + batch_noise
+                
                 if self.train_config.random_noise_shift > 0.0:
                     # get random noise -1 to 1
                     noise_shift = torch.randn(
diff --git a/toolkit/config_modules.py b/toolkit/config_modules.py
index 51355fee..03c04cf1 100644
--- a/toolkit/config_modules.py
+++ b/toolkit/config_modules.py
@@ -398,6 +398,10 @@ class TrainConfig:
         self.target_noise_multiplier = kwargs.get('target_noise_multiplier', 1.0)
         self.random_noise_multiplier = kwargs.get('random_noise_multiplier', 0.0)
         self.do_signal_correction_noise = kwargs.get('do_signal_correction_noise', False)
+        # batch noise correction adds other images in the batch as noise to correct away from other images
+        self.do_batch_noise_correction = kwargs.get('do_batch_noise_correction', False)
+        self.batch_noise_correction_scale = kwargs.get('batch_noise_correction_scale', 0.1)
+        
         self.signal_correction_noise_scale = kwargs.get('signal_correction_noise_scale', 1.0)
         self.random_noise_shift = kwargs.get('random_noise_shift', 0.0)
         self.img_multiplier = kwargs.get('img_multiplier', 1.0)