diff --git a/cuburn/code/filters.py b/cuburn/code/filters.py
index f35c0d5..3167237 100644
--- a/cuburn/code/filters.py
+++ b/cuburn/code/filters.py
@@ -69,8 +69,9 @@ fma_buf(float4 *dst, const float4 *src, int astride, float scale) {
 }
 ''')
 
-denblurlib = devlib(decls='''
-texture<float,  cudaTextureType2D> blur_src;
+denblurlib = devlib(deps=[texshearlib], decls='''
+texture<float4, cudaTextureType2D> chan4_src;
+texture<float,  cudaTextureType2D> chan1_src;
 
 __constant__ float gauss_coefs[7] = {
     0.00443305f,  0.05400558f,  0.24203623f,  0.39905028f,
@@ -78,7 +79,7 @@ __constant__ float gauss_coefs[7] = {
 };
 ''', defs=r'''
 // Apply a Gaussian-esque blur to the density channel of the texture in
-// ``bilateral_src`` in the horizontal direction, and write it to ``dst``, a
+// ``chan4_src`` in the horizontal direction, and write it to ``dst``, a
 // one-channel buffer.
 __global__ void den_blur(float *dst, int pattern, int upsample) {
     int xi = blockIdx.x * blockDim.x + threadIdx.x;
@@ -89,7 +90,7 @@ __global__ void den_blur(float *dst, int pattern, int upsample) {
 
     #pragma unroll
     for (int i = 0; i < 7; i++)
-        den += tex_shear(bilateral_src, pattern, x, y, (i - 3) << upsample).w
+        den += tex_shear(chan4_src, pattern, x, y, (i - 3) << upsample).w
              * gauss_coefs[i];
     dst[yi * (blockDim.x * gridDim.x) + xi] = den;
 }
@@ -104,15 +105,13 @@ __global__ void den_blur_1c(float *dst, int pattern, int upsample) {
 
     #pragma unroll
     for (int i = 0; i < 7; i++)
-        den += tex_shear(blur_src, pattern, x, y, (i - 3) << upsample)
+        den += tex_shear(chan1_src, pattern, x, y, (i - 3) << upsample)
              * gauss_coefs[i];
     dst[yi * (blockDim.x * gridDim.x) + xi] = den;
 }
 ''')
 
-bilaterallib = devlib(deps=[logscalelib, texshearlib, denblurlib], decls='''
-texture<float4, cudaTextureType2D> bilateral_src;
-''', defs=r'''
+bilaterallib = devlib(deps=[logscalelib, texshearlib, denblurlib], defs=r'''
 /* sstd:    spatial standard deviation (Gaussian filter)
  * cstd:    color standard deviation (Gaussian on the range [0, 1], where 1
  *          represents an "opposite" color).
@@ -146,7 +145,7 @@ bilateral(float4 *dst, int pattern, int radius,
 
     // Gather the center point, and pre-average the color values for faster
     // comparison.
-    float4 cen = tex2D(bilateral_src, x, y);
+    float4 cen = tex2D(chan4_src, x, y);
     float cdrcp = 1.0f / (cen.w + 1.0e-6f);
     cen.x *= cdrcp;
     cen.y *= cdrcp;
@@ -160,13 +159,13 @@ bilateral(float4 *dst, int pattern, int radius,
     // Be extra-sure spatial coeffecients have been written
     __syncthreads();
 
-    float4 pix = tex_shear(bilateral_src, pattern, x, y, -radius - 1.0f);
-    float4 next = tex_shear(bilateral_src, pattern, x, y, -radius);
+    float4 pix = tex_shear(chan4_src, pattern, x, y, -radius - 1.0f);
+    float4 next = tex_shear(chan4_src, pattern, x, y, -radius);
 
     for (float r = -radius; r <= radius; r++) {
         float prev = pix.w;
         pix = next;
-        next = tex_shear(bilateral_src, pattern, x, y, r + 1.0f);
+        next = tex_shear(chan4_src, pattern, x, y, r + 1.0f);
 
         // This initial factor is arbitrary, but seems to do a decent job at
         // preventing excessive bleed-out from points inside an empty region.
@@ -201,7 +200,7 @@ bilateral(float4 *dst, int pattern, int radius,
         //
         // Note that both the gradient and the blurred weight are calculated
         // in one dimension, along the current sampling vector.
-        float avg = tex_shear(blur_src, pattern, x, y, r);
+        float avg = tex_shear(chan1_src, pattern, x, y, r);
         float gradfact = (next.w - prev) / (avg + 1.0e-6f);
         if (r < 0) gradfact = -gradfact;
         gradfact = exp2f(-exp2f(gspeed * gradfact));
diff --git a/cuburn/filters.py b/cuburn/filters.py
index d081b8f..1621a75 100644
--- a/cuburn/filters.py
+++ b/cuburn/filters.py
@@ -8,6 +8,18 @@ from pycuda.gpuarray import vec
 import code.filters
 from code.util import ClsMod, argset, launch
 
+def mktref(mod, n):
+    tref = mod.get_texref(n)
+    tref.set_filter_mode(cuda.filter_mode.POINT)
+    tref.set_address_mode(0, cuda.address_mode.WRAP)
+    tref.set_address_mode(1, cuda.address_mode.WRAP)
+    return tref
+
+def mkdsc(dim, ch):
+    return argset(cuda.ArrayDescriptor(), height=dim.ah,
+                  width=dim.astride, num_channels=ch,
+                  format=cuda.array_format.FLOAT)
+
 class Filter(object):
     def apply(self, fb, gnm, dim, tc, stream=None):
         """
@@ -34,20 +46,10 @@ class Bilateral(Filter, ClsMod):
         bs = sb * dim.ah
         bl, gr = (32, 8, 1), (dim.astride / 32, dim.ah / 8)
 
-        mkdsc = lambda c: argset(cuda.ArrayDescriptor(), height=dim.ah,
-                                 width=dim.astride, num_channels=c,
-                                 format=cuda.array_format.FLOAT)
-        def mktref(n):
-            tref = self.mod.get_texref(n)
-            tref.set_filter_mode(cuda.filter_mode.POINT)
-            tref.set_address_mode(0, cuda.address_mode.WRAP)
-            tref.set_address_mode(1, cuda.address_mode.WRAP)
-            return tref
-
-        dsc = mkdsc(4)
-        tref = mktref('bilateral_src')
-        grad_dsc = mkdsc(1)
-        grad_tref = mktref('blur_src')
+        dsc = mkdsc(dim, 4)
+        tref = mktref(self.mod, 'chan4_src')
+        grad_dsc = mkdsc(dim, 1)
+        grad_tref = mktref(self.mod, 'chan1_src')
 
         for pattern in range(self.directions):
             # Scale spatial parameter so that a "pixel" is equivalent to an