如何将带有4个以上波段的像素数组保存到java中的Tiff / GeoTiff文件中？
假设我手动为超过4个频段创建了像素值，我想将它们存储在 tiff 文件中。
这些波段可以是R，G，B，温度（温度值不在0到255的范围内，因此我使用int而不是pexils的字节）等等。任何可从卫星获取的信息
现在我想将这些像素保存到tiff文件中。在java中有一个BufferedImage类，它有很多类型，如：TYPE_4BYTE_ABGR，TYPE_BYTE_GRAY等。但它们都不适用于4个以上的多波段。有TYPE_CUSTOM，但是在指定它并试图保存时数据到Tiff文件它给你一个例外，因为它不支持写操作（仅用于读操作，即它可以读取文件并将类型设置为TYPE_CUSTOM，如果它不理解类型但它不能写文件在一个不理解的类型）。
以下代码适用于3个频段甚至不正确（它没有显示彩色图像，看起来像是一个缺失线条的扭曲图像）但是对于超过4个频段我该怎么做？
ImageOutputStream ios = ImageIO.createImageOutputStream(os);
Iterator<ImageWriter> writers = ImageIO.getImageWritersByFormatName("tiff");
ImageWriter writer = writers.next();
writer.setOutput(ios);
int index = 0;
int[] pixels = new int[width*height*numberOfBands];
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
for (int k = 0; k < numberOfBands; k++) {
pixels[index++] = //any values;
}
}
}
DataBuffer dataBuffer = new DataBufferInt(pixels, pixels.length);
// Create Raster
WritableRaster writableRaster = Raster.createBandedRaster
(dataBuffer, width, height,
width, // scanlineStride
new int[numberOfBands], // bankIndices,
new int[numberOfBands], // bandOffsets,
null); // location
// Create the image
BufferedImage bufferedImage = new BufferedImage
(width, height, BufferedImage.TYPE_BYTE_RGB);
bufferedImage.setData(writableRaster);
IIOImage iioImage = new IIOImage(bufferedImage, null, null);
ImageWriteParam param = writer.getDefaultWriteParam();
writer.write(null, iioImage, param);
我正在使用GeoTools
编辑： 根据@iant我更改了代码，但它只给出了空白的透明背景，即使我保持相同数量的波段，即3个波段。 @iant你能查看下面的代码吗？
package examples;
import java.awt.image.WritableRaster;
import java.io.File;
import java.io.IOException;
import javax.media.jai.RasterFactory;
import org.geotools.coverage.CoverageFactoryFinder;
import org.geotools.coverage.grid.GridCoordinates2D;
import org.geotools.coverage.grid.GridCoverage2D;
import org.geotools.coverage.grid.GridCoverageFactory;
import org.geotools.coverage.grid.GridEnvelope2D;
import org.geotools.coverage.grid.GridGeometry2D;
import org.geotools.coverage.grid.io.AbstractGridFormat;
import org.geotools.coverage.grid.io.OverviewPolicy;
import org.geotools.gce.geotiff.GeoTiffFormat;
import org.geotools.gce.geotiff.GeoTiffReader;
import org.opengis.coverage.grid.GridCoverageWriter;
import org.opengis.parameter.GeneralParameterValue;
import org.opengis.parameter.ParameterValue;
public class CreateTiffImageTest2 {
public static void main(String[] args) throws IOException {
File file = new File("/home/mosab/Desktop/input/tif.tif");
ParameterValue<OverviewPolicy> policy = AbstractGridFormat.OVERVIEW_POLICY.createValue();
policy.setValue(OverviewPolicy.IGNORE);
ParameterValue<String> gridsize = AbstractGridFormat.SUGGESTED_TILE_SIZE.createValue();
ParameterValue<Boolean> useJaiRead = AbstractGridFormat.USE_JAI_IMAGEREAD.createValue();
useJaiRead.setValue(true);
GeoTiffReader geoTiffReader = new GeoTiffReader(file);
GridCoverage2D cov = geoTiffReader.read(new GeneralParameterValue[] { policy, gridsize, useJaiRead });
GridGeometry2D geometry = cov.getGridGeometry();
GridEnvelope2D gridEnvelope = geometry.getGridRange2D();
int w = (int) gridEnvelope.getWidth();
int h = (int) gridEnvelope.getHeight();
WritableRaster writableRaster = RasterFactory.createBandedRaster(java.awt.image.DataBuffer.TYPE_DOUBLE, w, h, 3,
null);
double[] data = new double[3];
double[] dest = new double[3];
for (int i = 0; i < w; i++) {
for (int j = 0; j < h; j++) {
GridCoordinates2D coord = new GridCoordinates2D(i, j);
cov.evaluate(coord, dest);
data[0] = dest[0];
data[1] = dest[1];
data[2] = dest[2];
writableRaster.setPixel(i, j, data);
}
float perc = 100.0f * i / w;
if (i % 100 == 0) {
System.out.println("done " + perc);
}
}
// Wrap the raster as a Coverage
GridCoverageFactory factory = CoverageFactoryFinder.getGridCoverageFactory(null);
GridCoverage2D gc = factory.create("name", writableRaster, cov.getEnvelope());
File out = new File("/home/mosab/Desktop/input/tifgen.tif");
GeoTiffFormat format = new GeoTiffFormat();
GridCoverageWriter writer = format.getWriter(out);
try {
writer.write(gc, null);
writer.dispose();
} catch (IllegalArgumentException | IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
}
更新2：
import java.awt.image.BufferedImage;
import java.awt.image.WritableRaster;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;
import javax.media.jai.RasterFactory;
import org.geotools.coverage.CoverageFactoryFinder;
import org.geotools.coverage.grid.GridCoverage2D;
import org.geotools.coverage.grid.GridCoverageFactory;
import org.geotools.coverage.grid.io.AbstractGridFormat;
import org.geotools.coverage.grid.io.GridFormatFinder;
import org.geotools.factory.Hints;
import org.geotools.gce.geotiff.GeoTiffFormat;
import org.geotools.geometry.jts.ReferencedEnvelope;
import org.geotools.referencing.CRS;
import org.opengis.coverage.grid.GridCoverageWriter;
import org.opengis.geometry.MismatchedDimensionException;
import org.opengis.referencing.FactoryException;
import org.opengis.referencing.NoSuchAuthorityCodeException;
import org.opengis.referencing.crs.CoordinateReferenceSystem;
public class Test2 {
public static void print(Object o) {
System.out.println(o);
}
public static void main(String[] args)
throws MismatchedDimensionException, NoSuchAuthorityCodeException, FactoryException, IOException {
File out = new File("/home/mosab/Desktop/input/1.tif");
BufferedImage img = ImageIO.read(out);
// ColorModel colorModel = img.getColorModel(
WritableRaster raster = img.getRaster();
int w = img.getWidth();
int h = img.getHeight();
print("width = " + w);
print("heigh = " + h);
int numBands = raster.getNumBands();
WritableRaster writableRaster = RasterFactory.createBandedRaster(java.awt.image.DataBuffer.TYPE_INT, w, h, 3,
null);
//as I said pixels are created manually but I used here pixels from an image to check the approach
int[] data = new int[3];
for (int i = 0; i < w; i++) {
for (int j = 0; j < h; j++) {
for (int k = 0; k < numBands; k++) {
data[k] = raster.getSample(i, j, k);
}
writableRaster.setPixel(i, j, data);
}
}
GridCoverageFactory factory = CoverageFactoryFinder.getGridCoverageFactory(null);
CoordinateReferenceSystem crs = CRS.decode("EPSG:27700");
int llx = 500000;
int lly = 105000;
ReferencedEnvelope referencedEnvelope = new ReferencedEnvelope(llx, llx + (w * 10), lly, lly + (h * 10), crs);
GridCoverage2D gc = factory.create("name", writableRaster, referencedEnvelope);
AbstractGridFormat format = GridFormatFinder.findFormat(out);
Hints hints = null;
if (format instanceof GeoTiffFormat) {
hints = new Hints(Hints.FORCE_LONGITUDE_FIRST_AXIS_ORDER, Boolean.TRUE);
}
File out1 = new File("/home/mosab/Desktop/input/tifgen.tif");
GridCoverageWriter writer = format.getWriter(out1);
try {
writer.write(gc, null);
writer.dispose();
} catch (IllegalArgumentException | IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
}
注意：我使用了int类型和一个大小为3的数组，因为原始图像有RGB波段。
1 个答案:
答案 0 :(得分：2)
您需要使用其他工厂方法创建WritableRaster，该方法允许您设置所需的数据类型和波段数。
WritableRaster writableRaster = RasterFactory.createBandedRaster
(java.awt.image.DataBuffer.TYPE_DOUBLE,width,height,4,null);
double[] data = new double[4];
double[] dest = new double[3];
for(int i=0;i<width;i++) {
for(int j=0;j<height;j++) {
//basically anything you like to create the bands
GridCoordinates2D coord = new GridCoordinates2D(i, j);
//here I just grab the values of my base image and add them together
cov.evaluate(coord, dest);
data[0]=dest[0];
data[1] = dest[1];
data[2] = dest[2];
data[3] = (dest[0]+dest[1]+dest[2]);
// write them to the new raster
writableRaster.setPixel(i, j, data);
}
float perc = 100.0f*i/width;
if(i%100==0) {
System.out.println("done "+perc);
}
}
//Wrap the raster as a Coverage
GridCoverageFactory factory = CoverageFactoryFinder.getGridCoverageFactory(null);
GridCoverage2D gc = factory.create("name", writableRaster, cov.getEnvelope());
//write it out
File out = new File(outFile);
GridCoverageWriter writer = format.getWriter(out);
try {
writer.write(gc , null);
writer.dispose();
} catch (IllegalArgumentException | IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
<强>更新
如果您使用以下代码：
public void makeTestRaster() throws MismatchedDimensionException, NoSuchAuthorityCodeException, FactoryException {
int width = 1000;
int height = 1000;
WritableRaster writableRaster = RasterFactory.createBandedRaster(java.awt.image.DataBuffer.TYPE_DOUBLE, width,
height, 4, null);
double[] data = new double[4];
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
data[0] = i * 100.0;
data[1] = j * 100.0;
data[2] = (width - i) * 100.0;
data[3] = (height - j) * 100.0;
System.out.println(i + "," + j + ":" + data[0] + " " + data[1] + " " + data[2] + " " + data[3] + " ");
writableRaster.setPixel(i, j, data);
}
float perc = 100.0f * i / width;
if (i % 100 == 0) {
System.out.println("done " + perc);
}
}
File out = new File("test.tif");
GridCoverageFactory factory = CoverageFactoryFinder.getGridCoverageFactory(null);
CoordinateReferenceSystem crs = CRS.decode("EPSG:27700");
int llx = 500000;
int lly = 105000;
ReferencedEnvelope referencedEnvelope = new ReferencedEnvelope(llx, llx + (width * 10), lly, lly + (height * 10),
crs);
GridCoverage2D gc = factory.create("name", writableRaster, referencedEnvelope);
AbstractGridFormat format = GridFormatFinder.findFormat(out);
Hints hints = null;
if (format instanceof GeoTiffFormat) {
hints = new Hints(Hints.FORCE_LONGITUDE_FIRST_AXIS_ORDER, Boolean.TRUE);
}
GridCoverageWriter writer = format.getWriter(out);
try {
writer.write(gc, null);
writer.dispose();
} catch (IllegalArgumentException | IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
它创造了一个10公里的方形栅格（靠近我的房子）。它有4个乐队可以代表你喜欢的任何东西，在它上面运行gdalinfo会给出以下信息：
gdalinfo test.tif
Driver: GTiff/GeoTIFF
Files: test.tif
test.tif.aux.xml
Size is 1000, 1000
Coordinate System is:
PROJCS["OSGB 1936 / British National Grid",
GEOGCS["OSGB 1936",
DATUM["OSGB_1936",
SPHEROID["Airy 1830",6377563.396,299.3249646,
AUTHORITY["EPSG","7001"]],
TOWGS84[446.448,-125.157,542.06,0.15,0.247,0.842,-20.489],
AUTHORITY["EPSG","6277"]],
PRIMEM["Greenwich",0,
AUTHORITY["EPSG","8901"]],
UNIT["degree",0.0174532925199433,
AUTHORITY["EPSG","9122"]],
AUTHORITY["EPSG","4277"]],
PROJECTION["Transverse_Mercator"],
PARAMETER["latitude_of_origin",49],
PARAMETER["central_meridian",-2],
PARAMETER["scale_factor",0.9996012717],
PARAMETER["false_easting",400000],
PARAMETER["false_northing",-100000],
UNIT["metre",1,
AUTHORITY["EPSG","9001"]],
AXIS["Easting",EAST],
AXIS["Northing",NORTH],
AUTHORITY["EPSG","27700"]]
Origin = (500000.000000000000000,115000.000000000000000)
Pixel Size = (10.000000000000000,-10.000000000000000)
Metadata:
AREA_OR_POINT=Area
TIFFTAG_RESOLUTIONUNIT=1 (unitless)
TIFFTAG_XRESOLUTION=1
TIFFTAG_YRESOLUTION=1
Image Structure Metadata:
INTERLEAVE=PIXEL
Corner Coordinates:
Upper Left ( 500000.000, 115000.000) ( 0d34'37.20"W, 50d55'30.82"N)
Lower Left ( 500000.000, 105000.000) ( 0d34'47.05"W, 50d50' 7.16"N)
Upper Right ( 510000.000, 115000.000) ( 0d26' 5.12"W, 50d55'24.27"N)
Lower Right ( 510000.000, 105000.000) ( 0d26'15.95"W, 50d50' 0.62"N)
Center ( 505000.000, 110000.000) ( 0d30'26.33"W, 50d52'45.79"N)
Band 1 Block=1000x8 Type=Float64, ColorInterp=Gray
Min=0.000 Max=99900.000
Minimum=0.000, Maximum=99900.000, Mean=49950.000, StdDev=28867.499
Metadata:
STATISTICS_MAXIMUM=99900
STATISTICS_MEAN=49950
STATISTICS_MINIMUM=0
STATISTICS_STDDEV=28867.499025721
Band 2 Block=1000x8 Type=Float64, ColorInterp=Undefined
Min=0.000 Max=97500.000
Minimum=0.000, Maximum=97500.000, Mean=48750.000, StdDev=30378.926
Metadata:
STATISTICS_MAXIMUM=97500
STATISTICS_MEAN=48750
STATISTICS_MINIMUM=0
STATISTICS_STDDEV=30378.926358031
Band 3 Block=1000x8 Type=Float64, ColorInterp=Undefined
Min=0.000 Max=97402500.000
Minimum=0.000, Maximum=97402500.000, Mean=24350625.000, StdDev=22476916.605
Metadata:
STATISTICS_MAXIMUM=97402500
STATISTICS_MEAN=24350625
STATISTICS_MINIMUM=0
STATISTICS_STDDEV=22476916.605084
Band 4 Block=1000x8 Type=Float64, ColorInterp=Undefined
Min=2500.000 Max=100000.000
Minimum=2500.000, Maximum=100000.000, Mean=51250.000, StdDev=30378.926
Metadata:
STATISTICS_MAXIMUM=100000
STATISTICS_MEAN=51249.999999999
STATISTICS_MINIMUM=2500
STATISTICS_STDDEV=30378.926358031
这清楚地显示了4个乐队。最后，如果您将其导入QGIS以查看您有机会将4个乐队中的任何一个分配给红色，绿色和蓝带。
这会产生各种通常称为假色的图像，或者如果您正在查看组合时没有意义的物理测量，则可以选择单个色带的灰度。
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