diff --git a/libs/image/kis_convolution_painter.h b/libs/image/kis_convolution_painter.h
index 2db38414a7..0911bec934 100644
--- a/libs/image/kis_convolution_painter.h
+++ b/libs/image/kis_convolution_painter.h
@@ -1,104 +1,109 @@
 /*
  *  Copyright (c) 2005 Cyrille Berger <cberger@cberger.net>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 #ifndef KIS_CONVOLUTION_PAINTER_H_
 #define KIS_CONVOLUTION_PAINTER_H_
 
 #include "kis_types.h"
 #include "kis_painter.h"
 #include "kis_image.h"
 #include "kritaimage_export.h"
 
 template<class factory> class KisConvolutionWorker;
 
 
 enum KisConvolutionBorderOp {
     BORDER_IGNORE = 0, // read the pixels outside of the application rect
     BORDER_REPEAT = 1  // Use the border for the missing pixels
 };
 
 /**
  * @brief The KisConvolutionPainter class applies a convolution kernel to a paint device.
  *
  *
  * Note: https://bugs.kde.org/show_bug.cgi?id=220310 shows that there's something here
  * that we need to fix...
  */
 class KRITAIMAGE_EXPORT KisConvolutionPainter : public KisPainter
 {
 
 public:
 
     KisConvolutionPainter();
     KisConvolutionPainter(KisPaintDeviceSP device);
     KisConvolutionPainter(KisPaintDeviceSP device, KisSelectionSP selection);
 
     enum TestingEnginePreference {
         NONE,
         SPATIAL,
         FFTW
     };
 
 
     KisConvolutionPainter(KisPaintDeviceSP device, TestingEnginePreference enginePreference);
 
     /**
      * Convolve all channels in src using the specified kernel; there is only one kernel for all
-     * channels possible. By default the border pixels are not convolved, that is, convolving
-     * starts with at (x + kernel.width/2, y + kernel.height/2) and stops at w - (kernel.width/2)
-     * and h - (kernel.height/2)
+     * channels possible.
+     *
+     * WARNING: The painter will read **more** pixels than you pass in \p areaSize.
+     *          The actual processing area will be:
+     *          QRect(x - kernel.width() / 2,
+     *                y - kernel.height() / 2,
+     *                w + 2 * (kernel.width() / 2),
+     *                h + 2 * (kernel.height() / 2))
      *
      * The border op decides what to do with pixels too close to the edge of the rect as defined above.
      *
      * The channels flag determines which set out of color channels, alpha channels.
      * channels we convolve.
      *
      * Note that we do not (currently) support different kernels for
      * different channels _or_ channel types.
      *
      * If you want to convolve a subset of the channels in a pixel,
      * set those channels with KisPainter::setChannelFlags();
      */
     void applyMatrix(const KisConvolutionKernelSP kernel, const KisPaintDeviceSP src, QPoint srcPos, QPoint dstPos, QSize areaSize,
                      KisConvolutionBorderOp borderOp = BORDER_REPEAT);
 
     /**
      * The caller should ask if the painter needs an explicit transaction iff
      * the source and destination devices coincide. Otherwise, the transaction is
      * just not needed.
      */
     bool needsTransaction(const KisConvolutionKernelSP kernel) const;
 
     static bool supportsFFTW();
 
 protected:
     friend class KisConvolutionPainterTest;
 
 
 
 private:
     template<class factory>
         KisConvolutionWorker<factory>* createWorker(const KisConvolutionKernelSP kernel,
                                                     KisPainter *painter,
                                                     KoUpdater *progress);
 
      bool useFFTImplementation(const KisConvolutionKernelSP kernel) const;
 
 private:
     TestingEnginePreference m_enginePreference;
 };
 #endif //KIS_CONVOLUTION_PAINTER_H_
diff --git a/libs/image/kis_edge_detection_kernel.cpp b/libs/image/kis_edge_detection_kernel.cpp
index 2596140852..15ed4fc938 100644
--- a/libs/image/kis_edge_detection_kernel.cpp
+++ b/libs/image/kis_edge_detection_kernel.cpp
@@ -1,428 +1,414 @@
 /*
  *  Copyright (c) 2017 Wolthera van Hövell tot Westerflier <griffinvalley@gmail.com>
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
  *  the Free Software Foundation; either version 2 of the License, or
  *  (at your option) any later version.
  *
  *  This program is distributed in the hope that it will be useful,
  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  *  GNU General Public License for more details.
  *
  *  You should have received a copy of the GNU General Public License
  *  along with this program; if not, write to the Free Software
  *  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  */
 
 #include "kis_edge_detection_kernel.h"
 #include "kis_global.h"
 #include "kis_convolution_kernel.h"
 #include <kis_convolution_painter.h>
 #include <KoCompositeOpRegistry.h>
 #include <QRect>
 #include <KoColorSpace.h>
 #include <kis_iterator_ng.h>
 #include <QVector3D>
 
 KisEdgeDetectionKernel::KisEdgeDetectionKernel()
 {
 
 }
 /*
  * This code is very similar to the gaussian kernel code, except unlike the gaussian code,
  * edge-detection kernels DO use the diagonals.
  * Except for the simple mode. We implement the simple mode because it is an analog to
  * the old sobel filter.
  */
 
 Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> KisEdgeDetectionKernel::createHorizontalMatrix(qreal radius,
                                                                                                     FilterType type,
                                                                                                     bool reverse)
 {
     int kernelSize = kernelSizeFromRadius(radius);
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix(kernelSize, kernelSize);
 
     KIS_ASSERT_RECOVER_NOOP(kernelSize & 0x1);
     const int center = kernelSize / 2;
 
     if (type==Prewit) {
         for (int x = 0; x < kernelSize; x++) {
             for (int y=0; y<kernelSize; y++) {
                 qreal xDistance;
                 if (reverse) {
                     xDistance = x - center;
                 } else {
                     xDistance = center - x;
                 }
                 matrix(x, y) = xDistance;
             }
         }
     } else if(type==Simple) {
         matrix.resize(kernelSize, 1);
         for (int x = 0; x < kernelSize; x++) {
             qreal xDistance;
             if (reverse) {
                 xDistance = x - center;
             } else {
                 xDistance = center - x;
             }
             if (x==center) {
                 matrix(x, 0) = 0;
             } else {
                 matrix(x, 0) = (1/xDistance);
             }
         }
     } else {
         for (int x = 0; x < kernelSize; x++) {
             for (int y=0; y<kernelSize; y++) {
                 if (x==center && y==center) {
                     matrix(x, y) = 0;
                 } else {
                     qreal xD, yD;
                     if (reverse) {
                         xD = x - center;
                         yD = y - center;
                     } else {
                         xD = center - x;
                         yD = center - y;
                     }
                     matrix(x, y) = xD / (xD*xD + yD*yD);
                 }
             }
         }
     }
     return matrix;
 }
 
 Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> KisEdgeDetectionKernel::createVerticalMatrix(qreal radius,
                                                                                                   FilterType type,
                                                                                                   bool reverse)
 {
     int kernelSize = kernelSizeFromRadius(radius);
 
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix(kernelSize, kernelSize);
     KIS_ASSERT_RECOVER_NOOP(kernelSize & 0x1);
     const int center = kernelSize / 2;
 
     if (type==Prewit) {
         for (int y = 0; y < kernelSize; y++) {
             for (int x=0; x<kernelSize; x++) {
                 qreal yDistance;
                 if (reverse) {
                     yDistance = y - center;
                 } else {
                     yDistance = center - y;
                 }
                 matrix(x, y) = yDistance;
             }
         }
     } else if(type==Simple) {
         matrix.resize(1, kernelSize);
         for (int y = 0; y < kernelSize; y++) {
             qreal yDistance;
             if (reverse) {
                 yDistance = y - center;
             } else {
                 yDistance = center - y;
             }
             if (y==center) {
                 matrix(0, y) = 0;
             } else {
                 matrix(0, y) = (1/yDistance);
             }
         }
     } else {
         for (int y = 0; y < kernelSize; y++) {
             for (int x=0; x<kernelSize; x++) {
                 if (x==center && y==center) {
                     matrix(x, y) = 0;
                 } else {
                     qreal xD, yD;
                     if (reverse) {
                         xD = x - center;
                         yD = y - center;
                     } else {
                         xD = center - x;
                         yD = center - y;
                     }
                     matrix(x, y) = yD / (xD*xD + yD*yD);
                 }
             }
         }
     }
     return matrix;
 }
 
 KisConvolutionKernelSP KisEdgeDetectionKernel::createHorizontalKernel(qreal radius,
                                                                       KisEdgeDetectionKernel::FilterType type,
                                                                       bool denormalize,
                                                                       bool reverse)
 {
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix = createHorizontalMatrix(radius, type, reverse);
     if (denormalize) {
         return KisConvolutionKernel::fromMatrix(matrix, 0.5, 1);
     } else {
         return KisConvolutionKernel::fromMatrix(matrix, 0, matrix.sum());
     }
 }
 
 KisConvolutionKernelSP KisEdgeDetectionKernel::createVerticalKernel(qreal radius,
                                                                     KisEdgeDetectionKernel::FilterType type,
                                                                     bool denormalize,
                                                                     bool reverse)
 {
     Eigen::Matrix<qreal, Eigen::Dynamic, Eigen::Dynamic> matrix = createVerticalMatrix(radius, type, reverse);
     if (denormalize) {
         return KisConvolutionKernel::fromMatrix(matrix, 0.5, 1);
     } else {
         return KisConvolutionKernel::fromMatrix(matrix, 0, matrix.sum());
     }
 }
 
 int KisEdgeDetectionKernel::kernelSizeFromRadius(qreal radius)
 {
     return qMax((int)(2 * ceil(sigmaFromRadius(radius)) + 1), 3);
 }
 
 qreal KisEdgeDetectionKernel::sigmaFromRadius(qreal radius)
 {
     return 0.3 * radius + 0.3;
 }
 
 void KisEdgeDetectionKernel::applyEdgeDetection(KisPaintDeviceSP device,
                                                 const QRect &rect,
                                                 qreal xRadius,
                                                 qreal yRadius,
                                                 KisEdgeDetectionKernel::FilterType type,
                                                 const QBitArray &channelFlags,
                                                 KoUpdater *progressUpdater,
                                                 FilterOutput output,
                                                 bool writeToAlpha)
 {
     QPoint srcTopLeft = rect.topLeft();
     KisPainter finalPainter(device);
     finalPainter.setChannelFlags(channelFlags);
     finalPainter.setProgress(progressUpdater);
     if (output == pythagorean || output == radian) {
         KisPaintDeviceSP x_denormalised = new KisPaintDevice(device->colorSpace());
         KisPaintDeviceSP y_denormalised = new KisPaintDevice(device->colorSpace());
 
         x_denormalised->prepareClone(device);
         y_denormalised->prepareClone(device);
 
 
         KisConvolutionKernelSP kernelHorizLeftRight = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type);
         KisConvolutionKernelSP kernelVerticalTopBottom = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type);
 
-        qreal horizontalCenter = qreal(kernelHorizLeftRight->width()) / 2.0;
-        qreal verticalCenter = qreal(kernelVerticalTopBottom->height()) / 2.0;
-
         KisConvolutionPainter horizPainterLR(x_denormalised);
         horizPainterLR.setChannelFlags(channelFlags);
         horizPainterLR.setProgress(progressUpdater);
         horizPainterLR.applyMatrix(kernelHorizLeftRight, device,
-                                   srcTopLeft - QPoint(0, ceil(horizontalCenter)),
-                                   srcTopLeft - QPoint(0, ceil(horizontalCenter)),
-                                   rect.size() + QSize(0, 2 * ceil(horizontalCenter)), BORDER_REPEAT);
+                                   srcTopLeft,
+                                   srcTopLeft,
+                                   rect.size(), BORDER_REPEAT);
 
 
         KisConvolutionPainter verticalPainterTB(y_denormalised);
         verticalPainterTB.setChannelFlags(channelFlags);
         verticalPainterTB.setProgress(progressUpdater);
         verticalPainterTB.applyMatrix(kernelVerticalTopBottom, device,
-                                      srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                      srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                      rect.size() + QSize(0, 2 * ceil(verticalCenter)), BORDER_REPEAT);
+                                      srcTopLeft,
+                                      srcTopLeft,
+                                      rect.size(), BORDER_REPEAT);
 
         KisSequentialIterator yItterator(y_denormalised, rect);
         KisSequentialIterator xItterator(x_denormalised, rect);
         KisSequentialIterator finalIt(device, rect);
         const int pixelSize = device->colorSpace()->pixelSize();
         const int channels = device->colorSpace()->channelCount();
         const int alphaPos = device->colorSpace()->alphaPos();
         KIS_SAFE_ASSERT_RECOVER_RETURN(alphaPos >= 0);
 
         QVector<float> yNormalised(channels);
         QVector<float> xNormalised(channels);
         QVector<float> finalNorm(channels);
 
         while(yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
             device->colorSpace()->normalisedChannelsValue(yItterator.rawData(), yNormalised);
             device->colorSpace()->normalisedChannelsValue(xItterator.rawData(), xNormalised);
             device->colorSpace()->normalisedChannelsValue(finalIt.rawData(), finalNorm);
 
             if (output == pythagorean) {
                 for (int c = 0; c<channels; c++) {
                     finalNorm[c] = 2 * sqrt( ((xNormalised[c]-0.5)*(xNormalised[c]-0.5)) + ((yNormalised[c]-0.5)*(yNormalised[c]-0.5)));
                 }
             } else { //radian
                 for (int c = 0; c<channels; c++) {
                     finalNorm[c] = atan2(xNormalised[c]-0.5, yNormalised[c]-0.5);
                 }
             }
 
             if (writeToAlpha) {
                 KoColor col(finalIt.rawData(), device->colorSpace());
                 qreal alpha = 0;
 
                 for (int c = 0; c<(channels-1); c++) {
                     alpha = alpha+finalNorm[c];
                 }
 
                 alpha = qMin(alpha/(channels-1), col.opacityF());
                 col.setOpacity(alpha);
                 memcpy(finalIt.rawData(), col.data(), pixelSize);
             } else {
                 quint8* f = finalIt.rawData();
                 finalNorm[alphaPos] = 1.0;
                 device->colorSpace()->fromNormalisedChannelsValue(f, finalNorm);
                 memcpy(finalIt.rawData(), f, pixelSize);
             }
 
         }
     } else {
         KisConvolutionKernelSP kernel;
-        qreal center = 0;
         bool denormalize = !writeToAlpha;
         if (output == xGrowth) {
             kernel = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type, denormalize);
-            center = qreal(kernel->width()) / 2.0;
         } else if (output == xFall) {
             kernel = KisEdgeDetectionKernel::createHorizontalKernel(xRadius, type, denormalize, true);
-            center = qreal(kernel->width()) / 2.0;
         } else if (output == yGrowth) {
             kernel = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type, denormalize);
-            center = qreal(kernel->height()) / 2.0;
         } else { //yFall
             kernel = KisEdgeDetectionKernel::createVerticalKernel(yRadius, type, denormalize, true);
-            center = qreal(kernel->height()) / 2.0;
         }
 
         if (writeToAlpha) {
             KisPaintDeviceSP denormalised = new KisPaintDevice(device->colorSpace());
             denormalised->prepareClone(device);
 
             KisConvolutionPainter kernelP(denormalised);
             kernelP.setChannelFlags(channelFlags);
             kernelP.setProgress(progressUpdater);
             kernelP.applyMatrix(kernel, device,
-                                srcTopLeft - QPoint(0, ceil(center)),
-                                srcTopLeft - QPoint(0, ceil(center)),
-                                rect.size() + QSize(0, 2 * ceil(center)), BORDER_REPEAT);
+                                srcTopLeft, srcTopLeft,
+                                rect.size(), BORDER_REPEAT);
             KisSequentialIterator iterator(denormalised, rect);
             KisSequentialIterator finalIt(device, rect);
             const int pixelSize = device->colorSpace()->pixelSize();
             const int channels = device->colorSpace()->colorChannelCount();
             QVector<float> normalised(channels);
             while (iterator.nextPixel() && finalIt.nextPixel()) {
                 device->colorSpace()->normalisedChannelsValue(iterator.rawData(), normalised);
                 KoColor col(finalIt.rawData(), device->colorSpace());
                 qreal alpha = 0;
                 for (int c = 0; c<channels; c++) {
                     alpha = alpha+normalised[c];
                 }
                 alpha = qMin(alpha/channels, col.opacityF());
                 col.setOpacity(alpha);
                 memcpy(finalIt.rawData(), col.data(), pixelSize);
 
             }
 
         } else {
             KisConvolutionPainter kernelP(device);
             kernelP.setChannelFlags(channelFlags);
             kernelP.setProgress(progressUpdater);
             kernelP.applyMatrix(kernel, device,
-                                srcTopLeft - QPoint(0, ceil(center)),
-                                srcTopLeft - QPoint(0, ceil(center)),
-                                rect.size() + QSize(0, 2 * ceil(center)), BORDER_REPEAT);
+                                srcTopLeft, srcTopLeft,
+                                rect.size(), BORDER_REPEAT);
 
             KisSequentialIterator finalIt(device, rect);
             int numConseqPixels = finalIt.nConseqPixels();
             while (finalIt.nextPixels(numConseqPixels)) {
                 numConseqPixels = finalIt.nConseqPixels();
                 device->colorSpace()->setOpacity(finalIt.rawData(), 1.0, numConseqPixels);
             }
         }
     }
 }
 
 void KisEdgeDetectionKernel::convertToNormalMap(KisPaintDeviceSP device,
                                                 const QRect &rect,
                                                 qreal xRadius,
                                                 qreal yRadius,
                                                 KisEdgeDetectionKernel::FilterType type,
                                                 int channelToConvert,
                                                 QVector<int> channelOrder,
                                                 QVector<bool> channelFlip,
                                                 const QBitArray &channelFlags,
                                                 KoUpdater *progressUpdater)
 {
     QPoint srcTopLeft = rect.topLeft();
     KisPainter finalPainter(device);
     finalPainter.setChannelFlags(channelFlags);
     finalPainter.setProgress(progressUpdater);
     KisPaintDeviceSP x_denormalised = new KisPaintDevice(device->colorSpace());
     KisPaintDeviceSP y_denormalised = new KisPaintDevice(device->colorSpace());
     x_denormalised->prepareClone(device);
     y_denormalised->prepareClone(device);
 
     KisConvolutionKernelSP kernelHorizLeftRight = KisEdgeDetectionKernel::createHorizontalKernel(yRadius, type, true, !channelFlip[1]);
     KisConvolutionKernelSP kernelVerticalTopBottom = KisEdgeDetectionKernel::createVerticalKernel(xRadius, type, true, !channelFlip[0]);
 
-    qreal horizontalCenter = qreal(kernelHorizLeftRight->width()) / 2.0;
-    qreal verticalCenter = qreal(kernelVerticalTopBottom->height()) / 2.0;
-
     KisConvolutionPainter horizPainterLR(y_denormalised);
     horizPainterLR.setChannelFlags(channelFlags);
     horizPainterLR.setProgress(progressUpdater);
     horizPainterLR.applyMatrix(kernelHorizLeftRight, device,
-                               srcTopLeft - QPoint(ceil(horizontalCenter), 0),
-                               srcTopLeft - QPoint(ceil(horizontalCenter), 0),
-                               rect.size() + QSize(2 * ceil(horizontalCenter), 0), BORDER_REPEAT);
+                               srcTopLeft, srcTopLeft,
+                               rect.size(), BORDER_REPEAT);
 
 
     KisConvolutionPainter verticalPainterTB(x_denormalised);
     verticalPainterTB.setChannelFlags(channelFlags);
     verticalPainterTB.setProgress(progressUpdater);
     verticalPainterTB.applyMatrix(kernelVerticalTopBottom, device,
-                                  srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                  srcTopLeft - QPoint(0, ceil(verticalCenter)),
-                                  rect.size() + QSize(0, 2 * ceil(verticalCenter)), BORDER_REPEAT);
+                                  srcTopLeft,
+                                  srcTopLeft,
+                                  rect.size(), BORDER_REPEAT);
 
     KisSequentialIterator yItterator(y_denormalised, rect);
     KisSequentialIterator xItterator(x_denormalised, rect);
     KisSequentialIterator finalIt(device, rect);
     const int pixelSize = device->colorSpace()->pixelSize();
     const int channels = device->colorSpace()->channelCount();
     const int alphaPos = device->colorSpace()->alphaPos();
     KIS_SAFE_ASSERT_RECOVER_RETURN(alphaPos >= 0);
 
     QVector<float> yNormalised(channels);
     QVector<float> xNormalised(channels);
     QVector<float> finalNorm(channels);
 
     while(yItterator.nextPixel() && xItterator.nextPixel() && finalIt.nextPixel()) {
         device->colorSpace()->normalisedChannelsValue(yItterator.rawData(), yNormalised);
         device->colorSpace()->normalisedChannelsValue(xItterator.rawData(), xNormalised);
 
         qreal z = 1.0;
         if (channelFlip[2]==true){
             z=-1.0;
         }
         QVector3D normal = QVector3D((xNormalised[channelToConvert]-0.5)*2, (yNormalised[channelToConvert]-0.5)*2, z);
         normal.normalize();
         finalNorm.fill(1.0);
         for (int c = 0; c<3; c++) {
             finalNorm[device->colorSpace()->channels().at(channelOrder[c])->displayPosition()] = (normal[channelOrder[c]]/2)+0.5;
         }
 
         finalNorm[alphaPos]= 1.0;
 
         quint8* pixel = finalIt.rawData();
         device->colorSpace()->fromNormalisedChannelsValue(pixel, finalNorm);
         memcpy(finalIt.rawData(), pixel, pixelSize);
 
     }
 }