diff --git a/src/ImageProcessor/Filters/Convolution/Convolution2DFilter - Copy.cs b/src/ImageProcessor/Filters/Convolution/Convolution2DFilter - Copy.cs
new file mode 100644
index 000000000..d67b86462
--- /dev/null
+++ b/src/ImageProcessor/Filters/Convolution/Convolution2DFilter - Copy.cs	
@@ -0,0 +1,99 @@
+// <copyright file="Convolution2DFilter.cs" company="James South">
+// Copyright (c) James South and contributors.
+// Licensed under the Apache License, Version 2.0.
+// </copyright>
+
+namespace ImageProcessor.Filters
+{
+    using System;
+    using System.Threading.Tasks;
+
+    /// <summary>
+    /// Defines a filter that uses a matrix to perform convolution across two dimensions against an image.
+    /// </summary>
+    public abstract class Convolution2DFilter : ParallelImageProcessor
+    {
+        /// <summary>
+        /// Gets the horizontal gradient operator.
+        /// </summary>
+        public abstract float[,] KernelX { get; }
+
+        /// <summary>
+        /// Gets the vertical gradient operator.
+        /// </summary>
+        public abstract float[,] KernelY { get; }
+
+        /// <inheritdoc/>
+        protected override void Apply(ImageBase target, ImageBase source, Rectangle targetRectangle, Rectangle sourceRectangle, int startY, int endY)
+        {
+            float[,] kernelX = this.KernelX;
+            float[,] kernelY = this.KernelY;
+            int kernelYLength = kernelY.GetLength(0);
+            int kernelXLength = kernelX.GetLength(0);
+            int radiusY = kernelYLength >> 1;
+            int radiusX = kernelXLength >> 1;
+
+            int sourceY = sourceRectangle.Y;
+            int sourceBottom = sourceRectangle.Bottom;
+            int startX = sourceRectangle.X;
+            int endX = sourceRectangle.Right;
+            int maxY = sourceBottom - 1;
+            int maxX = endX - 1;
+
+            Parallel.For(
+                startY,
+                endY,
+                y =>
+                {
+                    if (y >= sourceY && y < sourceBottom)
+                    {
+                        for (int x = startX; x < endX; x++)
+                        {
+                            float rX = 0;
+                            float gX = 0;
+                            float bX = 0;
+                            float rY = 0;
+                            float gY = 0;
+                            float bY = 0;
+
+                            // Apply each matrix multiplier to the color components for each pixel.
+                            for (int fy = 0; fy < kernelYLength; fy++)
+                            {
+                                int fyr = fy - radiusY;
+                                int offsetY = y + fyr;
+
+                                offsetY = offsetY.Clamp(0, maxY);
+
+                                for (int fx = 0; fx < kernelXLength; fx++)
+                                {
+                                    int fxr = fx - radiusX;
+                                    int offsetX = x + fxr;
+
+                                    offsetX = offsetX.Clamp(0, maxX);
+                                 
+                                    Color currentColor = source[offsetX, offsetY];
+                                    float r = currentColor.R;
+                                    float g = currentColor.G;
+                                    float b = currentColor.B;
+
+                                    rX += kernelX[fx, fy] * r;
+                                    gX += kernelX[fx, fy] * g;
+                                    bX += kernelX[fx, fy] * b;
+
+                                    rY += kernelY[fy, fx] * r;
+                                    gY += kernelY[fy, fx] * g;
+                                    bY += kernelY[fy, fx] * b;
+                                }
+                            }
+
+                            float red = (float)Math.Sqrt((rX * rX) + (rY * rY));
+                            float green = (float)Math.Sqrt((gX * gX) + (gY * gY));
+                            float blue = (float)Math.Sqrt((bX * bX) + (bY * bY));
+
+                            target[x, y] = new Color(red, green, blue);
+                        }
+                    }
+                });
+        }
+    }
+}
diff --git a/src/ImageProcessor/Filters/Convolution/GuassianBlur.cs b/src/ImageProcessor/Filters/Convolution/GuassianBlur.cs
index 37fa90173..d760221e3 100644
--- a/src/ImageProcessor/Filters/Convolution/GuassianBlur.cs
+++ b/src/ImageProcessor/Filters/Convolution/GuassianBlur.cs
@@ -1,14 +1,16 @@
 namespace ImageProcessor.Filters.Convolution
 {
     using System;
-    using System.Runtime.CompilerServices;
 
-    public class GuassianBlur : ConvolutionFilter
+    public class GuassianBlur : Convolution2DFilter
     {
         private int kernelSize;
 
         private float standardDeviation;
 
+        private float[,] kernelY;
+        private float[,] kernelX;
+
         /// <summary>
         /// Initializes a new instance of the <see cref="GuassianBlur"/> class.
         /// </summary>
@@ -18,81 +20,132 @@
         /// <param name="standardDeviation">
         /// The standard deviation 'sigma' value for calculating Gaussian curves.
         /// </param>
-        public GuassianBlur(int size, float standardDeviation)
+        public GuassianBlur(int size, float standardDeviation = 1.4f)
         {
             this.kernelSize = size;
             this.standardDeviation = standardDeviation;
         }
 
-        public override float[,] KernelX { get; }
+        /// <inheritdoc/>
+        public override float[,] KernelX => this.kernelX;
+
+        /// <inheritdoc/>
+        public override float[,] KernelY => this.kernelY;
+
+        /// <inheritdoc/>
+        protected override void OnApply(Rectangle targetRectangle, Rectangle sourceRectangle)
+        {
+            if (this.kernelY == null)
+            {
+                this.kernelY = this.CreateGaussianKernel(false);
+            }
+
+            if (this.kernelX == null)
+            {
+                this.kernelX = this.CreateGaussianKernel(true);
+            }
+        }
 
         /// <summary>
-        /// Create a 2 dimensional Gaussian kernel using the Gaussian G(x y) function for 
-        /// blurring images.
+        /// Create a 2 dimensional Gaussian kernel using the Gaussian G(x y) function
         /// </summary>
-        /// <param name="kernelSize">Kernel Size</param>
-        /// <returns>A Gaussian Kernel with the given size.</returns>
-        private float[,] CreateGuassianBlurFilter()
+        private void CreateGaussianKernel2D()
         {
-            // Create kernel
             int size = this.kernelSize;
-            float[,] kernel = this.CreateGaussianKernel2D(size);
-            float min = kernel[0, 0];
-
-            // Convert to integer blurring kernel. First of all the integer kernel is calculated from Kernel2D
-            // by dividing all elements by the element with the smallest value.
-            float[,] intKernel = new float[size, size];
-            int divider = 0;
+            float[,] kernel = new float[size, size];
 
+            int midpoint = size / 2;
+            float sum = 0;
             for (int i = 0; i < size; i++)
             {
+                int x = i - midpoint;
+
                 for (int j = 0; j < size; j++)
                 {
-                    float v = kernel[i, j] / min;
-
-                    if (v > ushort.MaxValue)
-                    {
-                        v = ushort.MaxValue;
-                    }
-
-                    intKernel[i, j] = (int)v;
-
-                    // Collect the divider
-                    divider += (int)intKernel[i, j];
+                    int y = j - midpoint;
+                    float gxy = this.Gaussian2D(x, y);
+                    sum += gxy;
+                    kernel[i, j] = gxy;
                 }
             }
 
-            // Update filter
-            //this.Divider = divider;
-            return intKernel;
+            // Normalise kernel so that the sum of all weights equals 1
+            //for (int i = 0; i < size; i++)
+            //{
+            //    for (int j = 0; j < size; j++)
+            //    {
+            //        kernel[i, 0] = kernel[i, j] / sum;
+            //    }
+            //}
+
+            this.kernelY = kernel;
         }
 
         /// <summary>
-        /// Create a 2 dimensional Gaussian kernel using the Gaussian G(x y) function
+        /// Create a 1 dimensional Gaussian kernel using the Gaussian G(x) function
         /// </summary>
-        /// <param name="kernelSize">Kernel Size</param>
-        /// <returns>A Gaussian Kernel with the given size and deviation.</returns>
-        public float[,] CreateGaussianKernel2D(int kernelSize)
+        /// <returns>The <see cref="T:float[,]"/></returns>
+        private float[,] CreateGaussianKernel(bool horizontal)
         {
-            float[,] kernel = new float[kernelSize, kernelSize];
-
-            int midpoint = kernelSize / 2;
+            int size = this.kernelSize;
+            float[,] kernel = horizontal ? new float[1, size] : new float[size, 1];
+            float sum = 0.0f;
 
-            for (int i = 0; i < kernelSize; i++)
+            int midpoint = size / 2;
+            for (int i = 0; i < size; i++)
             {
                 int x = i - midpoint;
+                float gx = this.Gaussian(x);
+                sum += gx;
+                if (horizontal)
+                {
+                    kernel[0, i] = gx;
+                }
+                else
+                {
+                    kernel[i, 0] = gx;
+                }
+            }
 
-                for (int j = 0; j < kernelSize; j++)
+            // Normalise kernel so that the sum of all weights equals 1
+            if (horizontal)
+            {
+                for (int i = 0; i < size; i++)
                 {
-                    int y = j - midpoint;
-                    float gxy = this.Gaussian2D(x, y);
-                    kernel[i, j] = gxy;
+                    kernel[0, i] = kernel[0, i] / sum;
+                }
+            }
+            else
+            {
+                for (int i = 0; i < size; i++)
+                {
+                    kernel[i, 0] = kernel[i, 0] / sum;
                 }
             }
 
             return kernel;
         }
 
+        /// <summary>
+        /// Implementation of 1D Gaussian G(x) function
+        /// </summary>
+        /// <param name="x">The x provided to G(x)</param>
+        /// <returns>The Gaussian G(x)</returns>
+        private float Gaussian(float x)
+        {
+            const float Numerator = 1.0f;
+            float deviation = this.standardDeviation;
+            float denominator = (float)(Math.Sqrt(2 * Math.PI) * deviation);
+
+            float exponentNumerator = -x * x;
+            float exponentDenominator = (float)(2 * Math.Pow(deviation, 2));
+
+            float left = Numerator / denominator;
+            float right = (float)Math.Exp(exponentNumerator / exponentDenominator);
+
+            return left * right;
+        }
+
         /// <summary>
         /// Implementation of 2D Gaussian G(x) function
         /// </summary>
@@ -102,10 +155,12 @@
         private float Gaussian2D(float x, float y)
         {
             const float Numerator = 1.0f;
-            float denominator = (float)((2 * Math.PI) * Math.Pow(this.standardDeviation, 2));
+            float deviation = this.standardDeviation;
+            double pow = Math.Pow(deviation, 2);
+            float denominator = (float)((2 * Math.PI) * pow);
 
             float exponentNumerator = (-x * x) + (-y * y);
-            float exponentDenominator = (float)(2 * Math.Pow(this.standardDeviation, 2));
+            float exponentDenominator = (float)(2 * pow);
 
             float left = Numerator / denominator;
             float right = (float)Math.Exp(exponentNumerator / exponentDenominator);
diff --git a/src/ImageProcessor/project.lock.json.REMOVED.git-id b/src/ImageProcessor/project.lock.json.REMOVED.git-id
index dba2656f5..24339fed2 100644
--- a/src/ImageProcessor/project.lock.json.REMOVED.git-id
+++ b/src/ImageProcessor/project.lock.json.REMOVED.git-id
@@ -1 +1 @@
-eb00c54ee74016c2b70f81963e7e8f83cb2dd54b
\ No newline at end of file
+3f05708641eb3ed085d4689aae4a960eb067fd16
\ No newline at end of file
diff --git a/tests/ImageProcessor.Tests/Processors/Filters/FilterTests.cs b/tests/ImageProcessor.Tests/Processors/Filters/FilterTests.cs
index c5fb051d7..204210249 100644
--- a/tests/ImageProcessor.Tests/Processors/Filters/FilterTests.cs
+++ b/tests/ImageProcessor.Tests/Processors/Filters/FilterTests.cs
@@ -3,8 +3,10 @@ namespace ImageProcessor.Tests
 {
     using System.Diagnostics;
     using System.IO;
+    using System.Numerics;
 
     using ImageProcessor.Filters;
+    using ImageProcessor.Filters.Convolution;
 
     using Xunit;
 
@@ -12,31 +14,32 @@ namespace ImageProcessor.Tests
     {
         public static readonly TheoryData<string, IImageProcessor> Filters = new TheoryData<string, IImageProcessor>
         {
-            { "Brightness-50", new Brightness(50) },
-            { "Brightness--50", new Brightness(-50) },
-            { "Contrast-50", new Contrast(50) },
-            { "Contrast--50", new Contrast(-50) },
-            { "Blend", new Blend(new Image(File.OpenRead("../../TestImages/Formats/Bmp/Car.bmp")),15)},
-            { "Saturation-50", new Saturation(50) },
-            { "Saturation--50", new Saturation(-50) },
-            { "Alpha--50", new Alpha(50) },
-            { "Invert", new Invert() },
-            { "Sepia", new Sepia() },
-            { "BlackWhite", new BlackWhite() },
-            { "Lomograph", new Lomograph() },
-            { "Polaroid", new Polaroid() },
-            { "Kodachrome", new Kodachrome() },
-            { "GreyscaleBt709", new GreyscaleBt709() },
-            { "GreyscaleBt601", new GreyscaleBt601() },
-            { "Kayyali", new Kayyali() },
-            { "Kirsch", new Kirsch() },
-            { "Laplacian3X3", new Laplacian3X3() },
-            { "Laplacian5X5", new Laplacian5X5() },
-            { "LaplacianOfGaussian", new LaplacianOfGaussian() },
-            { "Prewitt", new Prewitt() },
-            { "RobertsCross", new RobertsCross() },
-            { "Scharr", new Scharr() },
-            { "Sobel", new Sobel() }
+            //{ "Brightness-50", new Brightness(50) },
+            //{ "Brightness--50", new Brightness(-50) },
+            //{ "Contrast-50", new Contrast(50) },
+            //{ "Contrast--50", new Contrast(-50) },
+            //{ "Blend", new Blend(new Image(File.OpenRead("../../TestImages/Formats/Bmp/Car.bmp")),15)},
+            //{ "Saturation-50", new Saturation(50) },
+            //{ "Saturation--50", new Saturation(-50) },
+            //{ "Alpha--50", new Alpha(50) },
+            //{ "Invert", new Invert() },
+            //{ "Sepia", new Sepia() },
+            //{ "BlackWhite", new BlackWhite() },
+            //{ "Lomograph", new Lomograph() },
+            //{ "Polaroid", new Polaroid() },
+            //{ "Kodachrome", new Kodachrome() },
+            //{ "GreyscaleBt709", new GreyscaleBt709() },
+            //{ "GreyscaleBt601", new GreyscaleBt601() },
+            //{ "Kayyali", new Kayyali() },
+            //{ "Kirsch", new Kirsch() },
+            //{ "Laplacian3X3", new Laplacian3X3() },
+            //{ "Laplacian5X5", new Laplacian5X5() },
+            //{ "LaplacianOfGaussian", new LaplacianOfGaussian() },
+            //{ "Prewitt", new Prewitt() },
+            //{ "RobertsCross", new RobertsCross() },
+            //{ "Scharr", new Scharr() },
+            //{ "Sobel", new Sobel() },
+            { "GuassianBlur", new GuassianBlur(20) }
         };
 
         [Theory]
diff --git a/tests/ImageProcessor.Tests/Processors/ProcessorTestBase.cs b/tests/ImageProcessor.Tests/Processors/ProcessorTestBase.cs
index 0e33d5438..7ba500e5e 100644
--- a/tests/ImageProcessor.Tests/Processors/ProcessorTestBase.cs
+++ b/tests/ImageProcessor.Tests/Processors/ProcessorTestBase.cs
@@ -19,20 +19,21 @@ namespace ImageProcessor.Tests
         /// </summary>
         public static readonly List<string> Files = new List<string>
         {
-            "../../TestImages/Formats/Jpg/Backdrop.jpg",
-            "../../TestImages/Formats/Jpg/Calliphora.jpg",
-            "../../TestImages/Formats/Jpg/lomo.jpg",
-            "../../TestImages/Formats/Jpg/shaftesbury.jpg",
-            "../../TestImages/Formats/Jpg/gamma_dalai_lama_gray.jpg",
-            "../../TestImages/Formats/Jpg/greyscale.jpg",
-            "../../TestImages/Formats/Bmp/Car.bmp",
-            "../../TestImages/Formats/Png/cmyk.png",
-            "../../TestImages/Formats/Png/gamma-1.0-or-2.2.png",
-            "../../TestImages/Formats/Png/splash.png",
-            "../../TestImages/Formats/Gif/leaf.gif",
-            "../../TestImages/Formats/Gif/rings.gif",
-            "../../TestImages/Formats/Gif/ani2.gif",
-            "../../TestImages/Formats/Gif/giphy.gif"
+            //"../../TestImages/Formats/Jpg/Backdrop.jpg",
+            //"../../TestImages/Formats/Jpg/Calliphora.jpg",
+            "../../TestImages/Formats/Jpg/ant.jpg",
+            //"../../TestImages/Formats/Jpg/lomo.jpg",
+            //"../../TestImages/Formats/Jpg/shaftesbury.jpg",
+            //"../../TestImages/Formats/Jpg/gamma_dalai_lama_gray.jpg",
+            //"../../TestImages/Formats/Jpg/greyscale.jpg",
+            //"../../TestImages/Formats/Bmp/Car.bmp",
+            //"../../TestImages/Formats/Png/cmyk.png",
+            //"../../TestImages/Formats/Png/gamma-1.0-or-2.2.png",
+            //"../../TestImages/Formats/Png/splash.png",
+            //"../../TestImages/Formats/Gif/leaf.gif",
+            //"../../TestImages/Formats/Gif/rings.gif",
+            //"../../TestImages/Formats/Gif/ani2.gif",
+            //"../../TestImages/Formats/Gif/giphy.gif"
         };
     }
 }
diff --git a/tests/ImageProcessor.Tests/TestImages/Formats/Jpg/ant.jpg.REMOVED.git-id b/tests/ImageProcessor.Tests/TestImages/Formats/Jpg/ant.jpg.REMOVED.git-id
new file mode 100644
index 000000000..1485b2316
--- /dev/null
+++ b/tests/ImageProcessor.Tests/TestImages/Formats/Jpg/ant.jpg.REMOVED.git-id
@@ -0,0 +1 @@
+1da0ed59ed220f32d72b01e6cbb9c73a7f3b9b35
\ No newline at end of file