diff --git a/filters.go b/filters.go
index 3bf29d2..27b57ec 100644
--- a/filters.go
+++ b/filters.go
@@ -142,6 +142,35 @@ func createFilter(img image.Image, factor [2]float32, size int, kernel func(floa
 	return
 }
 
+// Return a filter kernel that performs nearly identically to the provided
+// kernel, but generates and uses a precomputed table rather than executing
+// the kernel for each evaluation. The table is generated with tableSize
+// values that cover the kernal domain from -maxX to +maxX. The input kernel
+// is assumed to be symmetrical around 0, so the table only includes values
+// from 0 to maxX.
+func tableKernel(kernel func(float32) float32, tableSize int,
+	maxX float32) func(float32) float32 {
+
+	// precompute an array of filter coefficients
+	weights := make([]float32, tableSize+1)
+	for i := range weights {
+		weights[i] = kernel(maxX * float32(i) / float32(tableSize))
+	}
+	weights[tableSize] = 0.0
+
+	return func(x float32) float32 {
+		if x < 0.0 {
+			x = -x
+		}
+		indf := x / maxX * float32(tableSize)
+		ind := int(indf)
+		if ind >= tableSize {
+			return 0.0
+		}
+		return weights[ind] + (weights[ind+1]-weights[ind])*(indf-float32(ind))
+	}
+}
+
 // Nearest-neighbor interpolation
 func NearestNeighbor(img image.Image, factor [2]float32) Filter {
 	return createFilter(img, factor, 2, func(x float32) (y float32) {
@@ -213,12 +242,16 @@ func lanczosKernel(a uint) func(float32) float32 {
 	}
 }
 
+const lanczosTableSize = 300
+
 // Lanczos interpolation (a=2)
 func Lanczos2(img image.Image, factor [2]float32) Filter {
-	return createFilter(img, factor, 4, lanczosKernel(2))
+	return createFilter(img, factor, 4,
+		tableKernel(lanczosKernel(2), lanczosTableSize, 2.0))
 }
 
 // Lanczos interpolation (a=3)
 func Lanczos3(img image.Image, factor [2]float32) Filter {
-	return createFilter(img, factor, 6, lanczosKernel(3))
+	return createFilter(img, factor, 6,
+		tableKernel(lanczosKernel(3), lanczosTableSize, 3.0))
 }