diff --git a/src/merge.cpp b/src/merge.cpp
index 7c2afe9..4d90d4d 100644
--- a/src/merge.cpp
+++ b/src/merge.cpp
@@ -376,9 +376,12 @@ std::pair<double, double> merge::getNoiseParams( int ISO, \
                                           int white_level, \
                                           double black_level ) 
 {
+    // 4.1 Noise Parameters and RMS
+    // Noise parameters calculated from baseline ISO noise parameters
     double lambda_shot, lambda_read;
     std::tie(lambda_shot, lambda_read) = burst_images.bayer_images[burst_images.reference_image_idx].get_noise_params();
 
+    // 4.2-4.4 Denoising and Merging
     // Get padded bayer image
     cv::Mat reference_image = burst_images.bayer_images_pad[burst_images.reference_image_idx];
     // cv::imwrite("ref.jpg", reference_image);
@@ -411,7 +414,7 @@ std::pair<double, double> merge::getNoiseParams( int ISO, \
         // cv::imwrite("ref" + std::to_string(i) + ".jpg", channel_i);
 
         // Apply merging on the channel
-        cv::Mat merged_channel = processChannel(burst_images, alignments, channel_i);
+        cv::Mat merged_channel = processChannel(burst_images, alignments, channel_i, lambda_shot, lambda_read);
         // cv::imwrite("merged" + std::to_string(i) + ".jpg", merged_channel);
 
         // Put channel raw data back to channels
@@ -516,14 +519,39 @@ cv::Mat merge::mergeTiles(std::vector<cv::Mat> tiles, int num_rows, int num_cols
 
 cv::Mat merge::processChannel( hdrplus::burst& burst_images, \
                       std::vector<std::vector<std::vector<std::pair<int, int>>>>& alignments, \
-                      cv::Mat channel_image) {
-
+                      cv::Mat channel_image, \
+                      float lambda_shot, \
+                      float lambda_read) {
+    // Get tiles of the reference image
     std::vector<cv::Mat> reference_tiles = getReferenceTiles(channel_image);
 
-    // TODO: Temporal Denoising
+    // Get noise variance (sigma**2 = lambda_shot * tileRMS + lambda_read)
+    std::vector<float> noise_variance = getNoiseVariance(reference_tiles, lambda_shot, lambda_read);
+
+    // Apply FFT on reference tiles (spatial to frequency)
+    std::vector<cv::Mat> reference_tiles_DFT;
+    for (auto ref_tile : reference_tiles) {
+        cv::Mat ref_tile_DFT;
+        ref_tile.convertTo(ref_tile_DFT, CV_32F);
+        cv::dft(ref_tile_DFT, ref_tile_DFT, cv::DFT_SCALE|cv::DFT_COMPLEX_OUTPUT);
+        reference_tiles_DFT.push_back(ref_tile_DFT);
+    }
+
+    // TODO: 4.2 Temporal Denoising
+
+    // TODO: 4.3 Spatial Denoising
 
-    // TODO: Spatial Denoising
+    // Apply IFFT on reference tiles (frequency to spatial)
+    std::vector<cv::Mat> denoised_tiles;
+    for (auto dft_tile : reference_tiles_DFT) {
+        cv::Mat denoised_tile;
+        cv::dft(dft_tile, denoised_tile, cv::DFT_INVERSE|cv::DFT_REAL_OUTPUT);
+        denoised_tile.convertTo(denoised_tile, CV_16U);
+        denoised_tiles.push_back(denoised_tile);
+    }
+    reference_tiles = denoised_tiles;
 
+    // 4.4 Cosine Window Merging
     // Process tiles through 2D cosine window
     std::vector<cv::Mat> windowed_tiles;
     for (auto tile : reference_tiles) {