final 2024_Remote_Sensing

2024_Remote_Sensing/norm.py

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+import sys
+import rasterio
+import numpy as np
+
+def normalize_tif(input_tif, output_tif):
+    with rasterio.open(input_tif) as src:
+        data = src.read(1)  # Reading the first band
+        profile = src.profile
+
+        # Handle potential NoData values
+        valid_mask = data != src.nodata if src.nodata is not None else np.ones_like(data, dtype=bool)
+        data_min, data_max = data[valid_mask].min(), data[valid_mask].max()
+
+        # Normalize data
+        normalized_data = (data - data_min) / (data_max - data_min)
+        normalized_data[~valid_mask] = src.nodata  # Retain NoData values
+
+        profile.update(dtype=rasterio.float32)
+
+        with rasterio.open(output_tif, 'w', **profile) as dst:
+            dst.write(normalized_data.astype(rasterio.float32), 1)
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("Usage: python3 norm.py <input_tif> <output_tif>")
+        sys.exit(1)
+
+    input_file = sys.argv[1]
+    output_file = sys.argv[2]
+
+    normalize_tif(input_file, output_file)
+    print(f"Normalized file saved to {output_file}")