diff --git a/src/kbmod/file_utils.py b/src/kbmod/file_utils.py
deleted file mode 100644
index fcc1fdde..00000000
--- a/src/kbmod/file_utils.py
+++ /dev/null
@@ -1,70 +0,0 @@
-"""A collection of utility functions for working with files in KBMOD."""
-
-import csv
-import re
-from collections import OrderedDict
-from itertools import product
-from math import copysign
-from pathlib import Path
-
-import astropy.units as u
-import numpy as np
-from astropy.coordinates import *
-from astropy.io import fits
-from astropy.time import Time
-
-import kbmod.search as kb
-from kbmod.search import LayeredImage
-from kbmod.trajectory_utils import trajectory_from_np_object
-
-
-def load_deccam_layered_image(filename, psf):
-    """Load a layered image from the legacy deccam format.
-
-    Parameters
-    ----------
-    filename : `str`
-        The name of the file to load.
-    psf : `PSF`
-        The PSF to use for the image.
-
-    Returns
-    -------
-    img : `LayeredImage`
-        The loaded image.
-
-    Raises
-    ------
-    Raises a ``FileNotFoundError`` if the file does not exist.
-    Raises a ``ValueError`` if any of the validation checks fail.
-    """
-    if not Path(filename).is_file():
-        raise FileNotFoundError(f"{filename} not found")
-
-    img = None
-    with fits.open(filename) as hdul:
-        if len(hdul) < 4:
-            raise ValueError("Not enough extensions for legacy deccam format")
-
-        # Extract the obstime trying from a few keys and a few extensions.
-        obstime = -1.0
-        for key, ext in product(["MJD", "DATE-AVG", "MJD-OBS"], [0, 1]):
-            if key in hdul[ext].header:
-                value = hdul[ext].header[key]
-                if type(value) is float:
-                    obstime = value
-                    break
-                if type(value) is str:
-                    timesys = hdul[ext].header.get("TIMESYS", "UTC").lower()
-                    obstime = Time(value, scale=timesys).mjd
-                    break
-
-        img = LayeredImage(
-            hdul[1].data.astype(np.float32),  # Science
-            hdul[3].data.astype(np.float32),  # Variance
-            hdul[2].data.astype(np.float32),  # Mask
-            psf,
-            obstime,
-        )
-
-    return img