diff --git a/CHANGELOG.md b/CHANGELOG.md
index d60a80a42..bdafcf777 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,9 +1,11 @@
 # Change Log
 
-## Version 1.4.0
+## Unreleased
 
-### Changes
-- The image conversion task has been split into two packages, large_image_converter and large_image_tasks.  The tasks module is used with Girder and Girder Worker for converting images and depends on the converter package.  The converter package can be used as a stand-alone command line tool (#518)
+### Features
+- Multiple frames can be composited together with the style option
+
+## Version 1.4.0
 
 ### Features
 - Added a `canRead` method to the core module (#512)
@@ -11,7 +13,7 @@
 - Image conversion can now convert images readable by large_image sources but not by vips (#529)
 - Added an `open` method to the core module as an alias to `getTileSource` (#550)
 - Added an `open` method to each file source module (#550)
-- Numerous improvement to image converversion (#533, #535, #537, #541, #544, #545, #546, #549)
+- Numerous improvement to image conversion (#533, #535, #537, #541, #544, #545, #546, #549)
 
 ### Improvements
 - Better release bioformats resources (#502)
@@ -21,6 +23,9 @@
 - Support decoding JP2k compressed tiles in the tiff tile source (#514)
 - Hardened tests against transient timing issues (#532, #536)
 
+### Changes
+- The image conversion task has been split into two packages, large_image_converter and large_image_tasks.  The tasks module is used with Girder and Girder Worker for converting images and depends on the converter package.  The converter package can be used as a stand-alone command line tool (#518)
+
 ### Bug Fixes
 - Harden updates of the item view after making a large image (#508, #515)
 - Tiles in an unexpected color mode weren't consistently adjusted (#510)
diff --git a/docs/source/tilesource_options.rst b/docs/source/tilesource_options.rst
index 5d200c4ae..ad247d932 100644
--- a/docs/source/tilesource_options.rst
+++ b/docs/source/tilesource_options.rst
@@ -37,6 +37,8 @@ A band definition is an object which can contain the following keys:
 
 - ``band``: if -1 or None, the greyscale value is used.  Otherwise, a 1-based numerical index into the channels of the image or a string that matches the interpretation of the band ('red', 'green', 'blue', 'gray', 'alpha').  Note that 'gray' on an RGB or RGBA image will use the green band.
 
+- ``frame``: if specified, override the frame parameter used in the tile query for this band.  Note that it is more efficient to have at least one band not specify a frame parameter or use the same value as the basic query.  Defaults to the frame value of the core query.
+
 - ``min``: the value to map to the first palette value.  Defaults to 0.  'auto' to use 0 if the reported minimum and maximum of the band are between [0, 255] or use the reported minimum otherwise.  'min' or 'max' to always uses the reported minimum or maximum.
 
 - ``max``: the value to map to the last palette value.  Defaults to 255.  'auto' to use 0 if the reported minimum and maximum of the band are between [0, 255] or use the reported maximum otherwise.  'min' or 'max' to always uses the reported minimum or maximum.
diff --git a/large_image/tilesource/base.py b/large_image/tilesource/base.py
index 4d68eaa0f..e1f4158ac 100644
--- a/large_image/tilesource/base.py
+++ b/large_image/tilesource/base.py
@@ -6,7 +6,6 @@
 import PIL.Image
 import PIL.ImageColor
 import PIL.ImageDraw
-import random
 import threading
 import xml.etree.ElementTree
 from collections import defaultdict
@@ -500,6 +499,12 @@ def __init__(self, encoding='JPEG', jpegQuality=95, jpegSubsampling=0,
                     matches the interpretation of the band ('red', 'green',
                     'blue', 'gray', 'alpha').  Note that 'gray' on an RGB or
                     RGBA image will use the green band.
+                frame: if specified, override the frame value for this band.
+                    When used as part of a bands list, this can be used to
+                    composite multiple frames together.  It is most efficient
+                    if at least one band either doesn't specify a frame
+                    parameter or specifies the same frame value as the primary
+                    query.
                 min: the value to map to the first palette value.  Defaults to
                     0.  'auto' to use 0 if the reported minimum and maximum of
                     the band are between [0, 255] or use the reported minimum
@@ -1269,7 +1274,7 @@ def _scanForMinMax(self, dtype, frame=None, analysisSize=1024, **kwargs):
         self._skipStyle = True
         # Divert the tile cache while querying unstyled tiles
         classkey = self._classkey
-        self._classkey = 'nocache' + str(random.random())
+        self._classkey = self._classkey + '__unstyled'
         try:
             self._bandRanges[frame] = self.histogram(
                 dtype=dtype,
@@ -1333,20 +1338,39 @@ def _getMinMax(self, minmax, value, dtype, bandidx=None, frame=None):
                 value = 255
         return float(value)
 
-    def _applyStyle(self, image, style, frame=None):
+    def _applyStyle(self, image, style, x, y, z, frame=None):
         """
         Apply a style to a numpy image.
 
         :param image: the image to modify.
         :param style: a style object.
+        :param x: the x tile position; used for multi-frame styles.
+        :param y: the y tile position; used for multi-frame styles.
+        :param z: the z tile position; used for multi-frame styles.
         :param frame: the frame to use for auto ranging.
         :returns: a styled image.
         """
         style = style['bands'] if 'bands' in style else [style]
         output = numpy.zeros((image.shape[0], image.shape[1], 4), numpy.float)
+        mainImage = image
+        mainFrame = frame
         for entry in style:
             bandidx = 0 if image.shape[2] <= 2 else 1
             band = None
+            if entry.get('frame') is None or entry.get('frame') == frame:
+                image = mainImage
+                frame = mainFrame
+            else:
+                frame = entry['frame']
+                self._skipStyle = True
+                # Divert the tile cache while querying unstyled tiles
+                classkey = self._classkey
+                self._classkey = self._classkey + '__unstyled'
+                try:
+                    image = self.getTile(x, y, z, frame=frame, numpyAllowed=True)
+                finally:
+                    del self._skipStyle
+                    self._classkey = classkey
             if (isinstance(entry.get('band'), int) and
                     entry['band'] >= 1 and entry['band'] <= image.shape[2]):
                 bandidx = entry['band'] - 1
@@ -1394,13 +1418,16 @@ def _applyStyle(self, image, style, frame=None):
                         output[:, :, channel], numpy.where(keep, clrs, 0))
         return output
 
-    def _outputTileNumpyStyle(self, tile, applyStyle, frame=None):
+    def _outputTileNumpyStyle(self, tile, applyStyle, x, y, z, frame=None):
         """
         Convert a tile to a NUMPY array.  Optionally apply the style to a tile.
         Always returns a NUMPY tile.
 
         :param tile: the tile to convert.
         :param applyStyle: if True and there is a style, apply it.
+        :param x: the x tile position; used for multi-frame styles.
+        :param y: the y tile position; used for multi-frame styles.
+        :param z: the z tile position; used for multi-frame styles.
         :param frame: the frame to use for auto-ranging.
         :returns: a numpy array and a target PIL image mode.
         """
@@ -1408,7 +1435,7 @@ def _outputTileNumpyStyle(self, tile, applyStyle, frame=None):
         if applyStyle and getattr(self, 'style', None):
             with self._styleLock:
                 if not getattr(self, '_skipStyle', False):
-                    tile = self._applyStyle(tile, self.style, frame)
+                    tile = self._applyStyle(tile, self.style, x, y, z, frame)
         if tile.shape[0] != self.tileHeight or tile.shape[1] != self.tileWidth:
             extend = numpy.zeros(
                 (self.tileHeight, self.tileWidth, tile.shape[2]),
@@ -1450,7 +1477,7 @@ def _outputTile(self, tile, tileEncoding, x, y, z, pilImageAllowed=False,
         mode = None
         if (numpyAllowed == 'always' or tileEncoding == TILE_FORMAT_NUMPY or
                 (applyStyle and getattr(self, 'style', None)) or isEdge):
-            tile, mode = self._outputTileNumpyStyle(tile, applyStyle, kwargs.get('frame'))
+            tile, mode = self._outputTileNumpyStyle(tile, applyStyle, x, y, z, kwargs.get('frame'))
         if isEdge:
             contentWidth = min(self.tileWidth,
                                sizeX - (maxX - self.tileWidth))
diff --git a/test/test_source_ometiff.py b/test/test_source_ometiff.py
index 9d6112697..609b41bcb 100644
--- a/test/test_source_ometiff.py
+++ b/test/test_source_ometiff.py
@@ -94,6 +94,40 @@ def testStyleAutoMinMax():
     assert image[240][128][0] < imageB[240][128][0]
 
 
+def testStyleFrame():
+    imagePath = utilities.externaldata('data/sample.ome.tif.sha512')
+    source = large_image_source_ometiff.open(
+        imagePath, style=json.dumps({'bands': [{
+            'palette': ['#000000', '#0000ff'],
+        }, {
+            'palette': ['#000000', '#00ff00'],
+        }]}))
+    image, _ = source.getRegion(
+        output={'maxWidth': 256, 'maxHeight': 256}, format=TILE_FORMAT_NUMPY, frame=1)
+    sourceB = large_image_source_ometiff.open(
+        imagePath, style=json.dumps({'bands': [{
+            'palette': ['#000000', '#0000ff'],
+        }, {
+            'frame': 1,
+            'palette': ['#000000', '#00ff00'],
+        }]}))
+    imageB, _ = sourceB.getRegion(
+        output={'maxWidth': 256, 'maxHeight': 256}, format=TILE_FORMAT_NUMPY, frame=1)
+    assert numpy.all(image == imageB)
+    assert image.shape == imageB.shape
+    sourceC = large_image_source_ometiff.open(
+        imagePath, style=json.dumps({'bands': [{
+            'palette': ['#000000', '#0000ff'],
+        }, {
+            'frame': 2,
+            'palette': ['#000000', '#00ff00'],
+        }]}))
+    imageC, _ = sourceC.getRegion(
+        output={'maxWidth': 256, 'maxHeight': 256}, format=TILE_FORMAT_NUMPY, frame=1)
+    assert numpy.any(image != imageC)
+    assert image.shape == imageC.shape
+
+
 def testInternalMetadata():
     imagePath = utilities.externaldata('data/sample.ome.tif.sha512')
     source = large_image_source_ometiff.open(imagePath)