diff --git a/src/ImageSharp/Processing/Processors/Convolution/BoxBlurProcessor{TPixel}.cs b/src/ImageSharp/Processing/Processors/Convolution/BoxBlurProcessor{TPixel}.cs
index 8c5358770c..5beadb0cee 100644
--- a/src/ImageSharp/Processing/Processors/Convolution/BoxBlurProcessor{TPixel}.cs
+++ b/src/ImageSharp/Processing/Processors/Convolution/BoxBlurProcessor{TPixel}.cs
@@ -1,6 +1,7 @@
 // Copyright (c) Six Labors.
 // Licensed under the Apache License, Version 2.0.
 
+using System;
 using SixLabors.ImageSharp.PixelFormats;
 
 namespace SixLabors.ImageSharp.Processing.Processors.Convolution
@@ -23,24 +24,18 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             : base(configuration, source, sourceRectangle)
         {
             int kernelSize = (definition.Radius * 2) + 1;
-            this.KernelX = CreateBoxKernel(kernelSize);
-            this.KernelY = this.KernelX.Transpose();
+            this.Kernel = CreateBoxKernel(kernelSize);
         }
 
         /// <summary>
-        /// Gets the horizontal gradient operator.
+        /// Gets the 1D convolution kernel.
         /// </summary>
-        public DenseMatrix<float> KernelX { get; }
-
-        /// <summary>
-        /// Gets the vertical gradient operator.
-        /// </summary>
-        public DenseMatrix<float> KernelY { get; }
+        public float[] Kernel { get; }
 
         /// <inheritdoc/>
         protected override void OnFrameApply(ImageFrame<TPixel> source)
         {
-            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.KernelX, this.KernelY, false, this.Source, this.SourceRectangle);
+            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.Kernel, false, this.Source, this.SourceRectangle);
 
             processor.Apply(source);
         }
@@ -50,10 +45,12 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
         /// </summary>
         /// <param name="kernelSize">The maximum size of the kernel in either direction.</param>
         /// <returns>The <see cref="DenseMatrix{T}"/>.</returns>
-        private static DenseMatrix<float> CreateBoxKernel(int kernelSize)
+        private static float[] CreateBoxKernel(int kernelSize)
         {
-            var kernel = new DenseMatrix<float>(kernelSize, 1);
-            kernel.Fill(1F / kernelSize);
+            var kernel = new float[kernelSize];
+
+            kernel.AsSpan().Fill(1F / kernelSize);
+
             return kernel;
         }
     }
diff --git a/src/ImageSharp/Processing/Processors/Convolution/Convolution2PassProcessor{TPixel}.cs b/src/ImageSharp/Processing/Processors/Convolution/Convolution2PassProcessor{TPixel}.cs
index c7f5c94dd2..9b7ed75808 100644
--- a/src/ImageSharp/Processing/Processors/Convolution/Convolution2PassProcessor{TPixel}.cs
+++ b/src/ImageSharp/Processing/Processors/Convolution/Convolution2PassProcessor{TPixel}.cs
@@ -22,34 +22,26 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
         /// Initializes a new instance of the <see cref="Convolution2PassProcessor{TPixel}"/> class.
         /// </summary>
         /// <param name="configuration">The configuration which allows altering default behaviour or extending the library.</param>
-        /// <param name="kernelX">The horizontal gradient operator.</param>
-        /// <param name="kernelY">The vertical gradient operator.</param>
+        /// <param name="kernel">The 1D convolution kernel.</param>
         /// <param name="preserveAlpha">Whether the convolution filter is applied to alpha as well as the color channels.</param>
         /// <param name="source">The source <see cref="Image{TPixel}"/> for the current processor instance.</param>
         /// <param name="sourceRectangle">The source area to process for the current processor instance.</param>
         public Convolution2PassProcessor(
             Configuration configuration,
-            in DenseMatrix<float> kernelX,
-            in DenseMatrix<float> kernelY,
+            float[] kernel,
             bool preserveAlpha,
             Image<TPixel> source,
             Rectangle sourceRectangle)
             : base(configuration, source, sourceRectangle)
         {
-            this.KernelX = kernelX;
-            this.KernelY = kernelY;
+            this.Kernel = kernel;
             this.PreserveAlpha = preserveAlpha;
         }
 
         /// <summary>
-        /// Gets the horizontal convolution kernel.
+        /// Gets the convolution kernel.
         /// </summary>
-        public DenseMatrix<float> KernelX { get; }
-
-        /// <summary>
-        /// Gets the vertical convolution kernel.
-        /// </summary>
-        public DenseMatrix<float> KernelY { get; }
+        public float[] Kernel { get; }
 
         /// <summary>
         /// Gets a value indicating whether the convolution filter is applied to alpha as well as the color channels.
@@ -71,7 +63,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             // the two 1D kernels represent, and reuse it across both convolution steps, like in the bokeh blur.
             using var mapXY = new KernelSamplingMap(this.Configuration.MemoryAllocator);
 
-            mapXY.BuildSamplingOffsetMap(this.KernelY.Rows, this.KernelX.Columns, interest);
+            mapXY.BuildSamplingOffsetMap(this.Kernel.Length, this.Kernel.Length, interest);
 
             // Horizontal convolution
             var horizontalOperation = new HorizontalConvolutionRowOperation(
@@ -79,7 +71,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 firstPassPixels,
                 source.PixelBuffer,
                 mapXY,
-                this.KernelX,
+                this.Kernel,
                 this.Configuration,
                 this.PreserveAlpha);
 
@@ -94,7 +86,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 source.PixelBuffer,
                 firstPassPixels,
                 mapXY,
-                this.KernelY,
+                this.Kernel,
                 this.Configuration,
                 this.PreserveAlpha);
 
@@ -113,7 +105,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             private readonly Buffer2D<TPixel> targetPixels;
             private readonly Buffer2D<TPixel> sourcePixels;
             private readonly KernelSamplingMap map;
-            private readonly DenseMatrix<float> kernelMatrix;
+            private readonly float[] kernel;
             private readonly Configuration configuration;
             private readonly bool preserveAlpha;
 
@@ -123,7 +115,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 Buffer2D<TPixel> targetPixels,
                 Buffer2D<TPixel> sourcePixels,
                 KernelSamplingMap map,
-                DenseMatrix<float> kernelMatrix,
+                float[] kernel,
                 Configuration configuration,
                 bool preserveAlpha)
             {
@@ -131,7 +123,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 this.targetPixels = targetPixels;
                 this.sourcePixels = sourcePixels;
                 this.map = map;
-                this.kernelMatrix = kernelMatrix;
+                this.kernel = kernel;
                 this.configuration = configuration;
                 this.preserveAlpha = preserveAlpha;
             }
@@ -156,7 +148,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 // Span is 2x bounds.
                 int boundsX = this.bounds.X;
                 int boundsWidth = this.bounds.Width;
-                int kernelSize = this.kernelMatrix.Columns;
+                int kernelSize = this.kernel.Length;
 
                 Span<Vector4> sourceBuffer = span.Slice(0, this.bounds.Width);
                 Span<Vector4> targetBuffer = span.Slice(this.bounds.Width);
@@ -170,7 +162,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 PixelOperations<TPixel>.Instance.ToVector4(this.configuration, sourceRow, sourceBuffer);
 
                 ref Vector4 sourceBase = ref MemoryMarshal.GetReference(sourceBuffer);
-                ref float kernelBase = ref this.kernelMatrix[0, 0];
+                ref float kernelBase = ref this.kernel[0];
                 ref int sampleColumnBase = ref MemoryMarshal.GetReference(this.map.GetColumnOffsetSpan());
 
                 for (int x = 0; x < sourceBuffer.Length; x++)
@@ -210,7 +202,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 // Span is 2x bounds.
                 int boundsX = this.bounds.X;
                 int boundsWidth = this.bounds.Width;
-                int kernelSize = this.kernelMatrix.Columns;
+                int kernelSize = this.kernel.Length;
 
                 Span<Vector4> sourceBuffer = span.Slice(0, this.bounds.Width);
                 Span<Vector4> targetBuffer = span.Slice(this.bounds.Width);
@@ -226,7 +218,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 Numerics.Premultiply(sourceBuffer);
 
                 ref Vector4 sourceBase = ref MemoryMarshal.GetReference(sourceBuffer);
-                ref float kernelBase = ref this.kernelMatrix[0, 0];
+                ref float kernelBase = ref this.kernel[0];
                 ref int sampleColumnBase = ref MemoryMarshal.GetReference(this.map.GetColumnOffsetSpan());
 
                 for (int x = 0; x < sourceBuffer.Length; x++)
@@ -261,7 +253,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             private readonly Buffer2D<TPixel> targetPixels;
             private readonly Buffer2D<TPixel> sourcePixels;
             private readonly KernelSamplingMap map;
-            private readonly DenseMatrix<float> kernelMatrix;
+            private readonly float[] kernel;
             private readonly Configuration configuration;
             private readonly bool preserveAlpha;
 
@@ -271,7 +263,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 Buffer2D<TPixel> targetPixels,
                 Buffer2D<TPixel> sourcePixels,
                 KernelSamplingMap map,
-                DenseMatrix<float> kernelMatrix,
+                float[] kernel,
                 Configuration configuration,
                 bool preserveAlpha)
             {
@@ -279,7 +271,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 this.targetPixels = targetPixels;
                 this.sourcePixels = sourcePixels;
                 this.map = map;
-                this.kernelMatrix = kernelMatrix;
+                this.kernel = kernel;
                 this.configuration = configuration;
                 this.preserveAlpha = preserveAlpha;
             }
@@ -304,7 +296,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 // Span is 2x bounds.
                 int boundsX = this.bounds.X;
                 int boundsWidth = this.bounds.Width;
-                int kernelSize = this.kernelMatrix.Rows;
+                int kernelSize = this.kernel.Length;
 
                 Span<Vector4> sourceBuffer = span.Slice(0, this.bounds.Width);
                 Span<Vector4> targetBuffer = span.Slice(this.bounds.Width);
@@ -315,7 +307,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 targetBuffer.Clear();
 
                 ref Vector4 targetBase = ref MemoryMarshal.GetReference(targetBuffer);
-                ref float kernelBase = ref this.kernelMatrix[0, 0];
+                ref float kernelBase = ref this.kernel[0];
 
                 Span<TPixel> sourceRow;
                 for (int kY = 0; kY < kernelSize; kY++)
@@ -358,19 +350,18 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 // Span is 2x bounds.
                 int boundsX = this.bounds.X;
                 int boundsWidth = this.bounds.Width;
-                int kernelSize = this.kernelMatrix.Rows;
+                int kernelSize = this.kernel.Length;
 
                 Span<Vector4> sourceBuffer = span.Slice(0, this.bounds.Width);
                 Span<Vector4> targetBuffer = span.Slice(this.bounds.Width);
 
-                var state = new ConvolutionState(in this.kernelMatrix, this.map);
-                ref int sampleRowBase = ref state.GetSampleRow(y - this.bounds.Y);
+                ref int sampleRowBase = ref Unsafe.Add(ref MemoryMarshal.GetReference(this.map.GetRowOffsetSpan()), (y - this.bounds.Y) * kernelSize);
 
                 // Clear the target buffer for each row run.
                 targetBuffer.Clear();
 
                 ref Vector4 targetBase = ref MemoryMarshal.GetReference(targetBuffer);
-                ref float kernelBase = ref this.kernelMatrix[0, 0];
+                ref float kernelBase = ref this.kernel[0];
 
                 for (int kY = 0; kY < kernelSize; kY++)
                 {
diff --git a/src/ImageSharp/Processing/Processors/Convolution/ConvolutionProcessorHelpers.cs b/src/ImageSharp/Processing/Processors/Convolution/ConvolutionProcessorHelpers.cs
index 9844f99563..f93cdabc47 100644
--- a/src/ImageSharp/Processing/Processors/Convolution/ConvolutionProcessorHelpers.cs
+++ b/src/ImageSharp/Processing/Processors/Convolution/ConvolutionProcessorHelpers.cs
@@ -12,17 +12,15 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
         /// See <see href="http://chemaguerra.com/gaussian-filter-radius/"/>.
         /// </summary>
         internal static int GetDefaultGaussianRadius(float sigma)
-        {
-            return (int)MathF.Ceiling(sigma * 3);
-        }
+            => (int)MathF.Ceiling(sigma * 3);
 
         /// <summary>
         /// Create a 1 dimensional Gaussian kernel using the Gaussian G(x) function.
         /// </summary>
-        /// <returns>The <see cref="DenseMatrix{T}"/>.</returns>
-        internal static DenseMatrix<float> CreateGaussianBlurKernel(int size, float weight)
+        /// <returns>The convolution kernel.</returns>
+        internal static float[] CreateGaussianBlurKernel(int size, float weight)
         {
-            var kernel = new DenseMatrix<float>(size, 1);
+            var kernel = new float[size];
 
             float sum = 0F;
             float midpoint = (size - 1) / 2F;
@@ -32,13 +30,13 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 float x = i - midpoint;
                 float gx = Numerics.Gaussian(x, weight);
                 sum += gx;
-                kernel[0, i] = gx;
+                kernel[i] = gx;
             }
 
             // Normalize kernel so that the sum of all weights equals 1
             for (int i = 0; i < size; i++)
             {
-                kernel[0, i] /= sum;
+                kernel[i] /= sum;
             }
 
             return kernel;
@@ -47,10 +45,10 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
         /// <summary>
         /// Create a 1 dimensional Gaussian kernel using the Gaussian G(x) function
         /// </summary>
-        /// <returns>The <see cref="DenseMatrix{T}"/>.</returns>
-        internal static DenseMatrix<float> CreateGaussianSharpenKernel(int size, float weight)
+        /// <returns>The convolution kernel.</returns>
+        internal static float[] CreateGaussianSharpenKernel(int size, float weight)
         {
-            var kernel = new DenseMatrix<float>(size, 1);
+            var kernel = new float[size];
 
             float sum = 0;
 
@@ -60,7 +58,7 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 float x = i - midpoint;
                 float gx = Numerics.Gaussian(x, weight);
                 sum += gx;
-                kernel[0, i] = gx;
+                kernel[i] = gx;
             }
 
             // Invert the kernel for sharpening.
@@ -70,19 +68,19 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
                 if (i == midpointRounded)
                 {
                     // Calculate central value
-                    kernel[0, i] = (2F * sum) - kernel[0, i];
+                    kernel[i] = (2F * sum) - kernel[i];
                 }
                 else
                 {
                     // invert value
-                    kernel[0, i] = -kernel[0, i];
+                    kernel[i] = -kernel[i];
                 }
             }
 
             // Normalize kernel so that the sum of all weights equals 1
             for (int i = 0; i < size; i++)
             {
-                kernel[0, i] /= sum;
+                kernel[i] /= sum;
             }
 
             return kernel;
diff --git a/src/ImageSharp/Processing/Processors/Convolution/GaussianBlurProcessor{TPixel}.cs b/src/ImageSharp/Processing/Processors/Convolution/GaussianBlurProcessor{TPixel}.cs
index a9b692a015..4ade01f914 100644
--- a/src/ImageSharp/Processing/Processors/Convolution/GaussianBlurProcessor{TPixel}.cs
+++ b/src/ImageSharp/Processing/Processors/Convolution/GaussianBlurProcessor{TPixel}.cs
@@ -27,24 +27,18 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             : base(configuration, source, sourceRectangle)
         {
             int kernelSize = (definition.Radius * 2) + 1;
-            this.KernelX = ConvolutionProcessorHelpers.CreateGaussianBlurKernel(kernelSize, definition.Sigma);
-            this.KernelY = this.KernelX.Transpose();
+            this.Kernel = ConvolutionProcessorHelpers.CreateGaussianBlurKernel(kernelSize, definition.Sigma);
         }
 
         /// <summary>
-        /// Gets the horizontal gradient operator.
+        /// Gets the 1D convolution kernel.
         /// </summary>
-        public DenseMatrix<float> KernelX { get; }
-
-        /// <summary>
-        /// Gets the vertical gradient operator.
-        /// </summary>
-        public DenseMatrix<float> KernelY { get; }
+        public float[] Kernel { get; }
 
         /// <inheritdoc/>
         protected override void OnFrameApply(ImageFrame<TPixel> source)
         {
-            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.KernelX, this.KernelY, false, this.Source, this.SourceRectangle);
+            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.Kernel, false, this.Source, this.SourceRectangle);
 
             processor.Apply(source);
         }
diff --git a/src/ImageSharp/Processing/Processors/Convolution/GaussianSharpenProcessor{TPixel}.cs b/src/ImageSharp/Processing/Processors/Convolution/GaussianSharpenProcessor{TPixel}.cs
index 5e20865e5c..73aaaec188 100644
--- a/src/ImageSharp/Processing/Processors/Convolution/GaussianSharpenProcessor{TPixel}.cs
+++ b/src/ImageSharp/Processing/Processors/Convolution/GaussianSharpenProcessor{TPixel}.cs
@@ -27,24 +27,18 @@ namespace SixLabors.ImageSharp.Processing.Processors.Convolution
             : base(configuration, source, sourceRectangle)
         {
             int kernelSize = (definition.Radius * 2) + 1;
-            this.KernelX = ConvolutionProcessorHelpers.CreateGaussianSharpenKernel(kernelSize, definition.Sigma);
-            this.KernelY = this.KernelX.Transpose();
+            this.Kernel = ConvolutionProcessorHelpers.CreateGaussianSharpenKernel(kernelSize, definition.Sigma);
         }
 
         /// <summary>
-        /// Gets the horizontal gradient operator.
+        /// Gets the 1D convolution kernel.
         /// </summary>
-        public DenseMatrix<float> KernelX { get; }
-
-        /// <summary>
-        /// Gets the vertical gradient operator.
-        /// </summary>
-        public DenseMatrix<float> KernelY { get; }
+        public float[] Kernel { get; }
 
         /// <inheritdoc/>
         protected override void OnFrameApply(ImageFrame<TPixel> source)
         {
-            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.KernelX, this.KernelY, false, this.Source, this.SourceRectangle);
+            using var processor = new Convolution2PassProcessor<TPixel>(this.Configuration, this.Kernel, false, this.Source, this.SourceRectangle);
 
             processor.Apply(source);
         }