diff --git a/image_analysis/CMakeLists.txt b/image_analysis/CMakeLists.txt
index b9d3f310..517844ec 100644
--- a/image_analysis/CMakeLists.txt
+++ b/image_analysis/CMakeLists.txt
@@ -1,3 +1,23 @@
+SET(MINIGLOG ON)
+SET(PROVIDE_UNINSTALL_TARGET OFF)
+SET(USE_CUDA OFF)
+SET(EIGENSPARSE ON)
+SET(LAPACK OFF)
+SET(SUITESPARSE OFF)
+
+# Prevent MKL/BLAS/LAPACK from being found (guarantees no MKL)
+SET(CMAKE_DISABLE_FIND_PACKAGE_MKL TRUE)
+SET(CERES_THREADING_MODEL "OFF")
+
+FetchContent_Declare(
+        ceres
+        GIT_REPOSITORY https://github.com/ceres-solver/ceres-solver
+        GIT_TAG 0c70ed3
+        EXCLUDE_FROM_ALL
+)
+
+FetchContent_MakeAvailable(ceres)
+
 ADD_LIBRARY(JFJochImageAnalysis STATIC
         MXAnalysisWithoutFPGA.cpp
         MXAnalysisWithoutFPGA.h
@@ -18,5 +38,6 @@ ADD_SUBDIRECTORY(bragg_prediction)
 ADD_SUBDIRECTORY(indexing)
 ADD_SUBDIRECTORY(geom_refinement)
 ADD_SUBDIRECTORY(lattice_search)
+ADD_SUBDIRECTORY(scale_merge)
 
 TARGET_LINK_LIBRARIES(JFJochImageAnalysis JFJochBraggPrediction JFJochBraggIntegration JFJochLatticeSearch JFJochIndexing JFJochSpotFinding JFJochCommon JFJochGeomRefinement gemmi)
diff --git a/image_analysis/geom_refinement/CMakeLists.txt b/image_analysis/geom_refinement/CMakeLists.txt
index e32becb5..a81b8b54 100644
--- a/image_analysis/geom_refinement/CMakeLists.txt
+++ b/image_analysis/geom_refinement/CMakeLists.txt
@@ -1,22 +1,3 @@
-SET(MINIGLOG ON)
-SET(PROVIDE_UNINSTALL_TARGET OFF)
-SET(USE_CUDA OFF)
-SET(EIGENSPARSE ON)
-SET(LAPACK OFF)
-SET(SUITESPARSE OFF)
-
-# Prevent MKL/BLAS/LAPACK from being found (guarantees no MKL)
-SET(CMAKE_DISABLE_FIND_PACKAGE_MKL TRUE)
-SET(CERES_THREADING_MODEL "OFF")
-
-FetchContent_Declare(
-        ceres
-        GIT_REPOSITORY https://github.com/ceres-solver/ceres-solver
-        GIT_TAG 0c70ed3
-        EXCLUDE_FROM_ALL
-)
-
-FetchContent_MakeAvailable(ceres)
 
 ADD_LIBRARY(JFJochGeomRefinement STATIC
         RingOptimizer.cpp
diff --git a/image_analysis/scale_merge/CMakeLists.txt b/image_analysis/scale_merge/CMakeLists.txt
new file mode 100644
index 00000000..8b8b99d7
--- /dev/null
+++ b/image_analysis/scale_merge/CMakeLists.txt
@@ -0,0 +1,2 @@
+ADD_LIBRARY(JFJochScaleMerge ScaleAndMerge.cpp ScaleAndMerge.h)
+TARGET_LINK_LIBRARIES(JFJochScaleMerge Ceres::ceres Eigen3::Eigen JFJochCommon)
\ No newline at end of file
diff --git a/image_analysis/scale_merge/ScaleAndMerge.cpp b/image_analysis/scale_merge/ScaleAndMerge.cpp
new file mode 100644
index 00000000..9d134fd2
--- /dev/null
+++ b/image_analysis/scale_merge/ScaleAndMerge.cpp
@@ -0,0 +1,347 @@
+// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
+// SPDX-License-Identifier: GPL-3.0-only
+
+#include "ScaleAndMerge.h"
+
+#include <ceres/ceres.h>
+
+#include <algorithm>
+#include <cmath>
+#include <limits>
+#include <stdexcept>
+#include <tuple>
+#include <unordered_map>
+#include <utility>
+#include <vector>
+
+namespace {
+
+struct HKLKey {
+    int64_t h = 0;
+    int64_t k = 0;
+    int64_t l = 0;
+    bool is_positive = true; // only relevant if opt.merge_friedel == false
+
+    bool operator==(const HKLKey& o) const noexcept {
+        return h == o.h && k == o.k && l == o.l && is_positive == o.is_positive;
+    }
+};
+
+struct HKLKeyHash {
+    size_t operator()(const HKLKey& key) const noexcept {
+        auto mix = [](uint64_t x) {
+            x ^= x >> 33;
+            x *= 0xff51afd7ed558ccdULL;
+            x ^= x >> 33;
+            x *= 0xc4ceb9fe1a85ec53ULL;
+            x ^= x >> 33;
+            return x;
+        };
+        const uint64_t a = static_cast<uint64_t>(key.h);
+        const uint64_t b = static_cast<uint64_t>(key.k);
+        const uint64_t c = static_cast<uint64_t>(key.l);
+        const uint64_t d = static_cast<uint64_t>(key.is_positive ? 1 : 0);
+        return static_cast<size_t>(mix(a) ^ (mix(b) << 1) ^ (mix(c) << 2) ^ (mix(d) << 3));
+    }
+};
+
+inline int RoundImageId(float image_number, double rounding_step) {
+    if (!(rounding_step > 0.0))
+        rounding_step = 1.0;
+    const double x = static_cast<double>(image_number) / rounding_step;
+    const double r = std::round(x) * rounding_step;
+    return static_cast<int>(std::llround(r / rounding_step));
+}
+
+inline double SafeSigma(double s, double min_sigma) {
+    if (!std::isfinite(s) || s <= 0.0)
+        return min_sigma;
+    return std::max(s, min_sigma);
+}
+
+inline double SafeD(double d) {
+    if (!std::isfinite(d) || d <= 0.0)
+        return std::numeric_limits<double>::quiet_NaN();
+    return d;
+}
+
+inline int SafeToInt(int64_t x) {
+    if (x < std::numeric_limits<int>::min() || x > std::numeric_limits<int>::max())
+        throw std::out_of_range("HKL index out of int range for Gemmi");
+    return static_cast<int>(x);
+}
+
+// Canonicalize HKL according to Gemmi Reciprocal ASU if space group is provided.
+// If merge_friedel==true -> Friedel mates collapse (key.is_positive always true).
+// If merge_friedel==false -> keep I+ vs I- separate by key.is_positive.
+inline HKLKey CanonicalizeHKLKey(const Reflection& r, const ScaleMergeOptions& opt) {
+    HKLKey key{};
+    key.h = r.h;
+    key.k = r.k;
+    key.l = r.l;
+    key.is_positive = true;
+
+    // If no SG provided, we can still optionally separate Friedel mates deterministically.
+    if (!opt.space_group.has_value()) {
+        if (!opt.merge_friedel) {
+            const HKLKey neg{-r.h, -r.k, -r.l, true};
+            const bool pos = std::tie(key.h, key.k, key.l) >= std::tie(neg.h, neg.k, neg.l);
+            if (!pos) {
+                key.h = -key.h;
+                key.k = -key.k;
+                key.l = -key.l;
+                key.is_positive = false;
+            }
+        }
+        return key;
+    }
+
+    const gemmi::SpaceGroup& sg = *opt.space_group;
+    const gemmi::GroupOps gops = sg.operations();
+    const gemmi::ReciprocalAsu rasu(&sg);
+
+    const gemmi::Op::Miller in{{SafeToInt(r.h), SafeToInt(r.k), SafeToInt(r.l)}};
+    const auto [asu_hkl, sign_plus] = rasu.to_asu_sign(in, gops);
+
+    key.h = asu_hkl[0];
+    key.k = asu_hkl[1];
+    key.l = asu_hkl[2];
+    key.is_positive = opt.merge_friedel ? true : sign_plus;
+    return key;
+}
+
+struct IntensityResidual {
+    IntensityResidual(double Iobs, double sigma, double s2, bool refine_b)
+        : Iobs_(Iobs), inv_sigma_(1.0 / sigma), s2_(s2), refine_b_(refine_b) {}
+
+    template <typename T>
+    bool operator()(const T* const log_k,
+                    const T* const b,
+                    const T* const log_Ihkl,
+                    T* residual) const {
+        const T k = ceres::exp(log_k[0]);
+        const T Ihkl = ceres::exp(log_Ihkl[0]);
+
+        T atten = T(1);
+        if (refine_b_) {
+            // I_pred = k * exp(-B*s^2) * I_hkl
+            atten = ceres::exp(-b[0] * T(s2_));
+        }
+
+        const T Ipred = k * atten * Ihkl;
+        residual[0] = (Ipred - T(Iobs_)) * T(inv_sigma_);
+        return true;
+    }
+
+    double Iobs_;
+    double inv_sigma_;
+    double s2_;
+    bool refine_b_;
+};
+
+} // namespace
+
+ScaleMergeResult ScaleAndMergeReflectionsCeres(const std::vector<Reflection>& observations,
+                                              const ScaleMergeOptions& opt) {
+    ScaleMergeResult out;
+
+    struct ObsRef {
+        const Reflection* r = nullptr;
+        int img_id = 0;     // rounded/quantized image id
+        int img_slot = -1;  // compact [0..nimg)
+        int hkl_slot = -1;  // compact [0..nhkl)
+        double s2 = 0.0;
+        double sigma = 0.0;
+    };
+
+    std::vector<ObsRef> obs;
+    obs.reserve(observations.size());
+
+    std::unordered_map<int, int> imgIdToSlot;
+    imgIdToSlot.reserve(256);
+
+    std::unordered_map<HKLKey, int, HKLKeyHash> hklToSlot;
+    hklToSlot.reserve(observations.size());
+
+    for (const auto& r : observations) {
+        const double d = SafeD(r.d);
+        if (!std::isfinite(d))
+            continue;
+        if (!std::isfinite(r.I))
+            continue;
+
+        const double sigma = SafeSigma(static_cast<double>(r.sigma), opt.min_sigma);
+        const double s2 = 1.0 / (d * d);
+
+        const int img_id = RoundImageId(r.image_number, opt.image_number_rounding);
+
+        int img_slot;
+        {
+            auto it = imgIdToSlot.find(img_id);
+            if (it == imgIdToSlot.end()) {
+                img_slot = static_cast<int>(imgIdToSlot.size());
+                imgIdToSlot.emplace(img_id, img_slot);
+            } else {
+                img_slot = it->second;
+            }
+        }
+
+        int hkl_slot;
+        try {
+            const HKLKey key = CanonicalizeHKLKey(r, opt);
+            auto it = hklToSlot.find(key);
+            if (it == hklToSlot.end()) {
+                hkl_slot = static_cast<int>(hklToSlot.size());
+                hklToSlot.emplace(key, hkl_slot);
+            } else {
+                hkl_slot = it->second;
+            }
+        } catch (...) {
+            continue; // skip problematic HKL
+        }
+
+        ObsRef o;
+        o.r = &r;
+        o.img_id = img_id;
+        o.img_slot = img_slot;
+        o.hkl_slot = hkl_slot;
+        o.s2 = s2;
+        o.sigma = sigma;
+        obs.push_back(o);
+    }
+
+    const int nimg = static_cast<int>(imgIdToSlot.size());
+    const int nhkl = static_cast<int>(hklToSlot.size());
+
+    out.image_scale_k.assign(nimg, 1.0);
+    out.image_b_factor.assign(nimg, 0.0);
+    out.image_ids.assign(nimg, 0);
+
+    for (const auto& kv : imgIdToSlot) {
+        out.image_ids[kv.second] = kv.first;
+    }
+
+    std::vector<double> log_k(nimg, 0.0);
+    std::vector<double> b(nimg, 0.0);
+    std::vector<double> log_Ihkl(nhkl, 0.0);
+
+    // Initialize Ihkl from per-HKL median of observed intensities.
+    {
+        std::vector<std::vector<double>> per_hkl_I(nhkl);
+        for (const auto& o : obs) {
+            per_hkl_I[o.hkl_slot].push_back(static_cast<double>(o.r->I));
+        }
+        for (int h = 0; h < nhkl; ++h) {
+            auto& v = per_hkl_I[h];
+            if (v.empty()) {
+                log_Ihkl[h] = std::log(std::max(opt.min_sigma, 1e-6));
+                continue;
+            }
+            std::nth_element(v.begin(), v.begin() + static_cast<long>(v.size() / 2), v.end());
+            double med = v[v.size() / 2];
+            if (!std::isfinite(med) || med <= opt.min_sigma)
+                med = opt.min_sigma;
+            log_Ihkl[h] = std::log(med);
+        }
+    }
+
+    ceres::Problem problem;
+
+    std::unique_ptr<ceres::LossFunction> loss;
+    if (opt.use_huber_loss) {
+        loss = std::make_unique<ceres::HuberLoss>(opt.huber_delta);
+    }
+
+    for (const auto& o : obs) {
+        const double Iobs = static_cast<double>(o.r->I);
+
+        auto* cost = new ceres::AutoDiffCostFunction<IntensityResidual, 1, 1, 1, 1>(
+            new IntensityResidual(Iobs, o.sigma, o.s2, opt.refine_b_factor));
+
+        problem.AddResidualBlock(cost,
+                                 loss.get(),
+                                 &log_k[o.img_slot],
+                                 &b[o.img_slot],
+                                 &log_Ihkl[o.hkl_slot]);
+    }
+
+    // Fix gauge freedom: anchor first image scale to 1.0
+    if (opt.fix_first_image_scale && nimg > 0) {
+        log_k[0] = 0.0;
+        problem.SetParameterBlockConstant(&log_k[0]);
+    }
+
+    if (!opt.refine_b_factor) {
+        for (int i = 0; i < nimg; ++i) {
+            b[i] = 0.0;
+            problem.SetParameterBlockConstant(&b[i]);
+        }
+    } else {
+        for (int i = 0; i < nimg; ++i) {
+            if (opt.b_min)
+                problem.SetParameterLowerBound(&b[i], 0, *opt.b_min);
+            if (opt.b_max)
+                problem.SetParameterUpperBound(&b[i], 0, *opt.b_max);
+        }
+    }
+
+    ceres::Solver::Options options;
+    options.linear_solver_type = ceres::SPARSE_NORMAL_CHOLESKY;
+    options.minimizer_progress_to_stdout = false;
+    options.logging_type = ceres::LoggingType::SILENT;
+    options.max_num_iterations = opt.max_num_iterations;
+    options.max_solver_time_in_seconds = opt.max_solver_time_s;
+
+    ceres::Solver::Summary summary;
+    ceres::Solve(options, &problem, &summary);
+
+    for (int i = 0; i < nimg; ++i) {
+        out.image_scale_k[i] = std::exp(log_k[i]);
+        out.image_b_factor[i] = opt.refine_b_factor ? b[i] : 0.0;
+    }
+
+    // Reverse maps for merged output
+    std::vector<HKLKey> slotToHKL(nhkl);
+    for (const auto& kv : hklToSlot) {
+        slotToHKL[kv.second] = kv.first;
+    }
+
+    // crude sigma estimate from model residual scatter
+    std::vector<int> n_per_hkl(nhkl, 0);
+    std::vector<double> ss_per_hkl(nhkl, 0.0);
+
+    for (const auto& o : obs) {
+        const int i = o.img_slot;
+        const int h = o.hkl_slot;
+
+        const double k = std::exp(log_k[i]);
+        const double atten = opt.refine_b_factor ? std::exp(-b[i] * o.s2) : 1.0;
+        const double Ihkl = std::exp(log_Ihkl[h]);
+
+        const double Ipred = k * atten * Ihkl;
+        const double r = (Ipred - static_cast<double>(o.r->I));
+
+        n_per_hkl[h] += 1;
+        ss_per_hkl[h] += r * r;
+    }
+
+    out.merged.reserve(nhkl);
+    for (int h = 0; h < nhkl; ++h) {
+        MergedReflection m{};
+        m.h = slotToHKL[h].h;
+        m.k = slotToHKL[h].k;
+        m.l = slotToHKL[h].l;
+        m.I = static_cast<float>(std::exp(log_Ihkl[h]));
+
+        if (n_per_hkl[h] >= 2) {
+            const double rms = std::sqrt(ss_per_hkl[h] / static_cast<double>(n_per_hkl[h] - 1));
+            m.sigma = static_cast<float>(rms / std::sqrt(static_cast<double>(n_per_hkl[h])));
+        } else {
+            m.sigma = std::numeric_limits<float>::quiet_NaN();
+        }
+
+        out.merged.push_back(m);
+    }
+
+    return out;
+}
\ No newline at end of file
diff --git a/image_analysis/scale_merge/ScaleAndMerge.h b/image_analysis/scale_merge/ScaleAndMerge.h
new file mode 100644
index 00000000..f14658df
--- /dev/null
+++ b/image_analysis/scale_merge/ScaleAndMerge.h
@@ -0,0 +1,55 @@
+// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
+// SPDX-License-Identifier: GPL-3.0-only
+
+#pragma once
+
+#include <vector>
+#include <cstdint>
+#include <optional>
+
+#include "../../common/Reflection.h"
+#include "gemmi/symmetry.hpp"
+
+struct ScaleMergeOptions {
+    bool refine_b_factor = true;
+
+    bool use_huber_loss = true;
+    double huber_delta = 2.0;
+
+    int max_num_iterations = 100;
+    double max_solver_time_s = 1.0;
+
+    double image_number_rounding = 1.0;
+    double min_sigma = 1e-3;
+
+    bool fix_first_image_scale = true;
+
+    std::optional<double> b_min = 0.0;
+    std::optional<double> b_max = 200.0;
+
+    // Symmetry canonicalization of HKL prior to merging/scaling.
+    // If not set, the routine uses raw HKL as-is.
+    std::optional<gemmi::SpaceGroup> space_group;
+
+    // If true, treat Friedel mates as equivalent (merge anomalous pairs).
+    // If false, keep them separate by including a sign flag in the HKL key.
+    bool merge_friedel = true;
+};
+
+struct MergedReflection {
+    int h;
+    int k;
+    int l;
+    double I;
+    double sigma;
+};
+
+struct ScaleMergeResult {
+    std::vector<MergedReflection> merged;
+    std::vector<double> image_scale_k;
+    std::vector<double> image_b_factor;
+    std::vector<int> image_ids;
+};
+
+ScaleMergeResult ScaleAndMergeReflectionsCeres(const std::vector<Reflection>& observations,
+                                              const ScaleMergeOptions& opt = {});