diff --git a/httomolibgpu/__init__.py b/httomolibgpu/__init__.py
index e1b85cef..36aa0a91 100644
--- a/httomolibgpu/__init__.py
+++ b/httomolibgpu/__init__.py
@@ -1,5 +1,6 @@
 from httomolibgpu.misc.utils import data_checker
 
+from httomolibgpu.misc.blend import seam_blend_stitched_data
 from httomolibgpu.misc.corr import median_filter, remove_outlier
 from httomolibgpu.misc.denoise import total_variation_ROF, total_variation_PD
 from httomolibgpu.misc.morph import sino_360_to_180, data_resampler
@@ -22,6 +23,7 @@
     SIRT3d_tomobar,
     CGLS3d_tomobar,
     FISTA3d_tomobar,
+    ADMM3d_tomobar,
 )
 
 from httomolibgpu.recon.rotation import find_center_vo, find_center_360, find_center_pc
diff --git a/httomolibgpu/misc/blend.py b/httomolibgpu/misc/blend.py
new file mode 100644
index 00000000..4ab84d1f
--- /dev/null
+++ b/httomolibgpu/misc/blend.py
@@ -0,0 +1,115 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# ---------------------------------------------------------------------------
+# Copyright 2023 Diamond Light Source Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ---------------------------------------------------------------------------
+# Created By  : Tomography Team at DLS <scientificsoftware@diamond.ac.uk>
+# Created Date: 5 August 2026
+# ---------------------------------------------------------------------------
+"""Module for data type morphing functions"""
+
+import numpy as np
+from httomolibgpu import cupywrapper
+
+cp = cupywrapper.cp
+cupy_run = cupywrapper.cupy_run
+
+from typing import Optional
+
+from httomolibgpu.misc.utils import (
+    __check_variable_type,
+    __check_if_data_3D_array,
+    __check_if_data_correct_type,
+    __check_if_positive_nonzero,
+)
+
+__all__ = [
+    "seam_blend_stitched_data",
+]
+
+
+def seam_blend_stitched_data(
+    data: cp.ndarray,
+    overlap: int,
+    seam_index: int = 2560,
+    shift_seam_index: Optional[int] = None,
+) -> cp.ndarray:
+    """
+    Function blends the seam present in the stitched projection data using the overlap value provided.
+    Used in HTTomo for seamless stitching of datasets coming from two different (PCO) cameras.
+
+    Parameters
+    ----------
+    data : cp.ndarray
+        3d CuPy array of the stitched data, assuming the following axis ["angles", "detY", "detX"].
+    overlap : int
+        Overlap between the LEFT and the RIGHT images of the stitched data. Usually known from the experiment.
+    seam_index : int
+        The horizontal index of the seam in the stitched data. Normally equals to the width of one frame/projection before the stitching.
+    shift_seam_index : optional, int
+        performs a shift of the 'seam index' that is introduced by the data cropping. This is an HTTomo related feature and should be ignored by users.
+    Raises
+    ----------
+        ValueError: When data is not 3D.
+
+    Returns
+    ----------
+        cp.ndarray: stitched data CuPy array without the seam.
+    """
+    ### Data and parameters checks ###
+    methods_name = "seam_blend_stitched_data"
+    __check_if_data_3D_array(data, methods_name)
+    __check_if_data_correct_type(
+        data,
+        accepted_type=["float64", "float32", "uint8", "uint16", "uint32"],
+        methods_name=methods_name,
+    )
+    __check_if_positive_nonzero(
+        seam_index,
+        "seam_index",
+        True,
+        True,
+        methods_name,
+    )
+    __check_variable_type(seam_index, [int], "seam_index", [], methods_name)
+    __check_variable_type(
+        shift_seam_index, [int, type(None)], "shift_seam_index", [], methods_name
+    )
+    ###################################
+
+    if shift_seam_index is None:
+        shift_seam_index = 0
+
+    seam_index -= shift_seam_index
+
+    angles_dim, detY, detX = data.shape
+    if seam_index < 0 or seam_index >= detX:
+        err_str = f"Seam index '{seam_index}' cannot be negative or larger than the horizontal dimension of the data '{detX}'. Check 'shift_seam_index'."
+        raise ValueError(err_str)
+
+    ramp = cp.asarray(np.linspace(0, 1, overlap))
+
+    blended_data = cp.empty((angles_dim, detY, detX - overlap), dtype=data.dtype)
+
+    blended_data[:, :, 0 : seam_index - overlap] = data[
+        :, :, 0 : seam_index - overlap
+    ]  # left side
+    blended_data[:, :, seam_index::] = data[:, :, seam_index + overlap :]  # right side
+    blended_data[:, :, seam_index - overlap : seam_index] = (
+        data[:, :, seam_index - overlap : seam_index] * ramp[::-1]
+        + data[:, :, seam_index : seam_index + overlap] * ramp
+    )  # overlap area
+
+    return blended_data
diff --git a/tests/conftest.py b/tests/conftest.py
index 578d5c25..5afdba38 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -75,6 +75,12 @@ def ensure_clean_memory():
     cache.clear()
 
 
+@pytest.fixture
+def data_stitched(test_data_path):
+    in_file = os.path.join(test_data_path, "stitched_blend30_seam151.npy")
+    return cp.asarray(np.load(in_file))
+
+
 @pytest.fixture
 def host_data(data_file):
     return np.copy(data_file["data"])
diff --git a/tests/test_data/stitched_blend30_seam151.npy b/tests/test_data/stitched_blend30_seam151.npy
new file mode 100644
index 00000000..b3b58ad1
Binary files /dev/null and b/tests/test_data/stitched_blend30_seam151.npy differ
diff --git a/tests/test_misc/test_blend.py b/tests/test_misc/test_blend.py
new file mode 100644
index 00000000..68ab154a
--- /dev/null
+++ b/tests/test_misc/test_blend.py
@@ -0,0 +1,26 @@
+import cupy as cp
+import numpy as np
+
+from httomolibgpu.misc.blend import seam_blend_stitched_data
+
+
+def test_seam_blend_stitched_data(data_stitched):
+    result = seam_blend_stitched_data(
+        data_stitched, overlap=20, seam_index=151, shift_seam_index=None
+    )
+
+    assert result.flags.c_contiguous
+    assert result.dtype == cp.uint16
+    assert result.shape == (300, 4, 280)
+    np.testing.assert_array_almost_equal(int(cp.mean(result)), 11520)
+
+
+def test_seam_blend_stitched_data_shift(data_stitched):
+    result = seam_blend_stitched_data(
+        data_stitched, overlap=20, seam_index=151, shift_seam_index=10
+    )
+
+    assert result.flags.c_contiguous
+    assert result.dtype == np.uint16
+    assert result.shape == (300, 4, 280)
+    np.testing.assert_array_almost_equal(int(cp.mean(result)), 11506)