拉普拉斯銳化算法是讀取目标像素上下左右四個像素值，将上下左右四個像素值分别減去目标像素值，再将結果之和加上目标像素值作為目标像素最後的值，也就是說當目标像素與周圍像素內插補點較大，那麼計算後會進一步拉大內插補點，突出圖像上物體邊緣部分，達到銳化效果。
一般jgp或者png格式圖像采用Java ImageIO直接讀取所有像素後進行拉普拉斯銳化即可，為了更友善讀取tif格式影像則需要引入gdal。使用gdal讀取tif影像基本資訊，擷取影像寬、高、通道數。一般彩色影像包含RGB三個通道或者還有一個表示透明度的阿爾法通道。RGB通道一般對應tif圖像1、2、3通道，阿爾法通道一般為第4通道。
讀取影像基本資訊：
gdal.AllRegister();
Dataset srcDataset = gdal.Open(srcImage.toString(), gdalconstConstants.GA_ReadOnly);
int width = srcDataset.getRasterXSize();
int height = srcDataset.getRasterYSize();
Driver driver = srcDataset.GetDriver();
int count = srcDataset.GetRasterCount();
對tif影像進行拉普拉斯銳化，首先讀取影像資訊後轉為BufferdImage，使用處理BufferdImage的拉普拉斯算法進行處理，之後再将BufferdImage轉為tif圖像。處理過程需要考慮到BufferdImage最大支援的圖像寬和高為26663，而tif格式正射影像沒有這一限制，那麼處理過程需要考慮tif影像寬高是否超限，可以設定當tif影像寬或高超過26000像素就對影像進行拆分處理，如果沒有超限則直接讀取tif影像并轉換為BufferdImage。
具體實作：
if (count <= 3) {
Dataset destDataset = driver.Create(destImage.toString(), width, height, count);
destDataset.SetMetadata(srcDataset.GetMetadata_Dict());
Band srcBandR = srcDataset.GetRasterBand(1);
Band srcBandG = srcDataset.GetRasterBand(2);
Band srcBandB = srcDataset.GetRasterBand(3);
Band destBandR = destDataset.GetRasterBand(1);
Band destBandG = destDataset.GetRasterBand(2);
Band destBandB = destDataset.GetRasterBand(3);
int xIndex = (int)(width / 26000);
int yIndex = (int)(height / 26000);
int innerWidth = width / (xIndex + 1);
int innerHeight = height / (yIndex + 1);
BufferedImage innerImage = new BufferedImage(innerWidth, innerHeight, BufferedImage.TYPE_INT_RGB);
for(int i = 0; i <= yIndex ; i ++) {
for(int j = 0; j <= xIndex ;j++) {
for (int y = 0; y < innerHeight; y++) {
int[] arrayR = new int[innerWidth];
int[] arrayG = new int[innerWidth];
int[] arrayB = new int[innerWidth];
srcBandR.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayR);
srcBandG.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayG);
srcBandB.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayB);
for (int x = 0; x < innerWidth; x++) {
int valueR = arrayR[x];
int valueG = arrayG[x];
int valueB = arrayB[x];
int rgb = (clamp((int) valueR) & 0xff) << 16 | (clamp((int) valueG) & 0xff) << 8
| (clamp((int) valueB) & 0xff);
innerImage.setRGB(x, y, rgb);
}
}
innerImage = new LaplacianSharpen().lapLaceSharp(innerImage);
for (int y = 0; y < innerHeight; y++) {
int[] arrayR = new int[innerWidth];
int[] arrayG = new int[innerWidth];
int[] arrayB = new int[innerWidth];
for (int x = 0; x < innerWidth; x++) {
int rgb = innerImage.getRGB(x, y);
int valueR = (rgb >> 16) & 0xff;
int valueG = (rgb >> 8) & 0xff;
int valueB = rgb & 0xff;
arrayR[x] = valueR;
arrayG[x] = valueG;
arrayB[x] = valueB;
}
destBandR.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayR);
destBandG.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayG);
destBandB.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayB);
}
}
}
driver.delete();
srcDataset.delete();
destDataset.delete();
}else {
Dataset destDataset = driver.Create(destImage.toString(), width, height, 4);
destDataset.SetMetadata(srcDataset.GetMetadata_Dict());
Band srcBandR = srcDataset.GetRasterBand(1);
Band srcBandG = srcDataset.GetRasterBand(2);
Band srcBandB = srcDataset.GetRasterBand(3);
Band destBandR = destDataset.GetRasterBand(1);
Band destBandG = destDataset.GetRasterBand(2);
Band destBandB = destDataset.GetRasterBand(3);
// 讀取資訊
int xIndex = (int)(width / 26000);
int yIndex = (int)(height / 26000);
int innerWidth = width / (xIndex + 1);
int innerHeight = height / (yIndex + 1);
BufferedImage innerImage = new BufferedImage(innerWidth, innerHeight, BufferedImage.TYPE_INT_RGB);
for(int i = 0; i <= yIndex ; i ++) {
for(int j = 0; j <= xIndex ;j++) {
for (int y = 0; y < innerHeight; y++) {
int[] arrayR = new int[innerWidth];
int[] arrayG = new int[innerWidth];
int[] arrayB = new int[innerWidth];
srcBandR.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayR);
srcBandG.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayG);
srcBandB.ReadRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayB);
for (int x = 0; x < innerWidth; x++) {
int valueR = arrayR[x];
int valueG = arrayG[x];
int valueB = arrayB[x];
int rgb = (clamp((int) valueR) & 0xff) << 16 | (clamp((int) valueG) & 0xff) << 8
| (clamp((int) valueB) & 0xff);
innerImage.setRGB(x, y, rgb);
}
}
innerImage = new LaplacianSharpen().lapLaceSharp(innerImage);
for (int y = 0; y < height; y++) {
int[] arrayR = new int[innerWidth];
int[] arrayG = new int[innerWidth];
int[] arrayB = new int[innerWidth];
for (int x = 0; x < innerWidth; x++) {
int rgb = innerImage.getRGB(x, y);
int valueR = (rgb >> 16) & 0xff;
int valueG = (rgb >> 8) & 0xff;
int valueB = rgb & 0xff;
arrayR[x] = valueR;
arrayG[x] = valueG;
arrayB[x] = valueB;
}
destBandR.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayR);
destBandG.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayG);
destBandB.WriteRaster(j * innerWidth, i * innerHeight + y, innerWidth, 1, arrayB);
}
}
}
Band srcBand = srcDataset.GetRasterBand(4);
Band destBand = destDataset.GetRasterBand(4);
for (int y = 0; y < height; y++) {
int[] array = new int[width];
srcBand.ReadRaster(0, y, width, 1, array);
destBand.WriteRaster(0, y, width, 1, array);
}
driver.delete();
srcDataset.delete();
destDataset.delete();
}
處理前影像：
處理後影像：
