Revision: 6462
http://sourceforge.net/p/jump-pilot/code/6462
Author: ma15569
Date: 2020-09-14 07:55:10 +0000 (Mon, 14 Sep 2020)
Log Message:
-----------
Changed method
Modified Paths:
--------------
core/trunk/src/org/openjump/core/rasterimage/algorithms/GenericRasterAlgorithm.java
core/trunk/src/org/openjump/core/rasterimage/algorithms/KernelAlgorithm.java
Modified:
core/trunk/src/org/openjump/core/rasterimage/algorithms/GenericRasterAlgorithm.java
===================================================================
---
core/trunk/src/org/openjump/core/rasterimage/algorithms/GenericRasterAlgorithm.java
2020-09-14 07:51:37 UTC (rev 6461)
+++
core/trunk/src/org/openjump/core/rasterimage/algorithms/GenericRasterAlgorithm.java
2020-09-14 07:55:10 UTC (rev 6462)
@@ -381,11 +381,12 @@
Exception {
final RasterImageIO rasterImageIO = new RasterImageIO();
- final Point point = RasterImageIO.getImageDimensions(inputFile
- .getAbsolutePath());
+ // final Point point = RasterImageIO.getImageDimensions(inputFile
+ // .getAbsolutePath());
+ // final Envelope env = RasterImageIO.getGeoReferencing(
+ // inputFile.getAbsolutePath(), true, point);
final Envelope env = RasterImageIO.getGeoReferencing(
- inputFile.getAbsolutePath(), true, point);
-
+ inputFile.getAbsolutePath());
final Viewport viewport = frame.getContext().getLayerViewPanel()
.getViewport();
final Resolution requestedRes = RasterImageIO
Modified:
core/trunk/src/org/openjump/core/rasterimage/algorithms/KernelAlgorithm.java
===================================================================
---
core/trunk/src/org/openjump/core/rasterimage/algorithms/KernelAlgorithm.java
2020-09-14 07:51:37 UTC (rev 6461)
+++
core/trunk/src/org/openjump/core/rasterimage/algorithms/KernelAlgorithm.java
2020-09-14 07:55:10 UTC (rev 6462)
@@ -1,6 +1,5 @@
package org.openjump.core.rasterimage.algorithms;
-import java.awt.Point;
import java.awt.geom.NoninvertibleTransformException;
import java.awt.image.BufferedImage;
import java.awt.image.BufferedImageOp;
@@ -115,12 +114,12 @@
public String Description02_Laplace = "Laplacian filters are often used
for edge detection. They are often applied to an image that has first been
smoothed to reduce its sensitivity to noise.";
public String Description03_LineDetection = "Line detection filters, like
the gradient filters, can be used to perform edge detection. You may get better
results if you apply a smoothing algorithm before an edge detection algorithm.";
public String Description04_Roberts = "Roberts filters uses two 2 by 2
kernels to measure gradients in opposing diagonal directions";
- public String Description05_Prewit = "Mathematically, the operator uses
two 3\xD73 kernels which are convolved with the original image to calculate
approximations of the derivatives - one for horizontal changes, and one for
vertical";
+ public String Description05_Prewit = "Mathematically, the operator uses
two 3�3 kernels which are convolved with the original image to calculate
approximations of the derivatives - one for horizontal changes, and one for
vertical";
public String Description06_Sharpening = "The Sharpening (high-pass)
filter accentuates the comparative difference in the values with its
neighbors.";
public String Description07_Smoothing = "Smoothing (low-pass) filters
smooth the data by reducing local variation and removing noise.The low-pass
filter calculates the average (mean) value for each neighborhood. ";
public String Description08_Point = "The point spread function portrays
the distribution of light from a point source through a lense. This will
introduce a slight blurring effect.";
public String Description08_Others = "Blur and Emboss filters";
- public String Description10_Sobel = "Sobel filters are used to edge
detection. The operator uses two 3\xD73 kernels which are convolved with the
original image to calculate approximations of the derivatives \x96 one for
horizontal changes, and one for vertical.";
+ public String Description10_Sobel = "Sobel filters are used to edge
detection. The operator uses two 3�3 kernels which are convolved with the
original image to calculate approximations of the derivatives � one for
horizontal changes, and one for vertical.";
public String S_gradientEast = "Gradient East";
public String S_gradientNord = "Gradient North";
@@ -194,7 +193,7 @@
public float[] roberts_horizontal = { 0f, -1f, 1f, 0f };
public float[] roberts_vertical = { -1f, 0f, 0f, 1f };
- //Mathematically, the operator uses two 3\xD73 kernels which are convolved
with the original image to calculate approximations of the derivatives - one
for horizontal changes, and one for vertical
+ //Mathematically, the operator uses two 3�3 kernels which are convolved
with the original image to calculate approximations of the derivatives - one
for horizontal changes, and one for vertical
public float[] prewitt_vertical = { -1f, 0f, 1f, -1f, 0f, 1f, -1f, 0f, 1f
};
public float[] prewitt_horizontal = { -1f, -1f, -1f, 0f, 0f, 0f, 1f, 1f,
1f };
@@ -329,11 +328,12 @@
Exception {
final RasterImageIO rasterImageIO = new RasterImageIO();
- final Point point = RasterImageIO.getImageDimensions(outFile
- .getAbsolutePath());
+ // final Point point = RasterImageIO.getImageDimensions(outFile
+ // .getAbsolutePath());
+ // final Envelope env = RasterImageIO.getGeoReferencing(
+ // outFile.getAbsolutePath(), true, point);
final Envelope env = RasterImageIO.getGeoReferencing(
- outFile.getAbsolutePath(), true, point);
-
+ outFile.getAbsolutePath());
final Viewport viewport = frame.getContext().getLayerViewPanel()
.getViewport();
final Resolution requestedRes = RasterImageIO
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