default channel order of OpenCV is BGR

producer/jpg.go

@@ -9,7 +9,7 @@ import (
 	"gocv.io/x/gocv"
 )
 
-func GTiffToJPG(ftiff, fjpg string) error {
+func GTiffToJPG(ftiff, fjpg string, reversed bool) error {
 	// 打开 TIFF 文件
 	ds, err := godal.Open(ftiff)
 	if err != nil {
@@ -20,62 +20,61 @@ func GTiffToJPG(ftiff, fjpg string) error {
 
 	bands := ds.Bands()
 	log.Infof("TIFF file %s has %d bands", ftiff, len(bands))
-	if len(bands) < 3 {
-		err = fmt.Errorf("TIFF file %s has less than 3 bands", ftiff)
-		log.Error(err)
-		return err
-	}
 
 	// 获取图像大小
 	width := bands[0].Structure().SizeX
 	height := bands[0].Structure().SizeY
+	bandsCnt := len(bands)
 
-	// 读取每个波段并转换为 8 位
-	img := gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC3)
-	for i := 1; i <= 3; i++ {
-		band := ds.Bands()[i-1]
+	// 创建 16 位图像矩阵
+	var img gocv.Mat
+	defer img.Close()
+	if bandsCnt == 1 {
+		img = gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC1)
+	} else {
+		bandsCnt = 3 // 只取前三个波段
+		img = gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC3)
+	}
+
+	// 读取每个波段并存储到图像矩阵中
+	for i := 0; i < bandsCnt; i++ {
+		band := bands[i]
 		data := make([]uint16, width*height)
 		err = band.Read(0, 0, data, width, height)
 		if err != nil {
-			log.Printf("Error reading band %d: %v", i, err)
+			fmt.Printf("Error reading band %d: %v\n", i, err)
 			return err
 		}
 
-		// 计算最小值和最大值
-		var minVal, maxVal uint16 = 65535, 0
-		for _, value := range data {
-			if value < minVal {
-				minVal = value
-			}
-			if value > maxVal {
-				maxVal = value
-			}
-		}
-
-		// 将 16 位数据缩放到 8 位并存储到图像的相应通道
+		// 将 16 位数据存储到图像的相应通道
 		for y := 0; y < height; y++ {
 			for x := 0; x < width; x++ {
 				value := data[y*width+x]
-				scaledValue := uint8(float64(value-minVal) / float64(maxVal-minVal) * 255)
-				img.SetUCharAt(y, x*3+(i-1), scaledValue)
+				img.SetShortAt(y, x*bandsCnt+i, int16(value))
 			}
 		}
-
-		// 将 16 位数据存储到图像的相应通道
-		// for y := 0; y < height; y++ {
-		// 	for x := 0; x < width; x++ {
-		// 		value := data[y*width+x]
-		// 		img.SetShortAt(y, x*3+(i-1), int16(value))
-		// 	}
-		// }
 	}
 
-	// 调整图像大小
-	resizedImg := gocv.NewMat()
-	gocv.Resize(img, &resizedImg, image.Point{X: 2336, Y: 2336}, 0, 0, gocv.InterpolationCubic)
+	// 重采样图像
+	gocv.Resize(img, &img, image.Point{X: img.Cols() / 2, Y: img.Rows() / 2}, 0, 0, gocv.InterpolationCubic)
 
-	// 保存为 JPG 文件
-	ok := gocv.IMWrite(fjpg, resizedImg)
+	// 创建 8 位图像矩阵
+	img8 := gocv.NewMat()
+	defer img8.Close()
+	if bandsCnt == 1 {
+		img.ConvertToWithParams(&img8, gocv.MatTypeCV8UC1, 1.0/256.0*2, 0)
+	} else {
+		img.ConvertToWithParams(&img8, gocv.MatTypeCV8UC3, 1.0/256.0*2, 0)
+		if reversed {
+			channels := gocv.Split(img8)
+			gocv.Merge([]gocv.Mat{channels[2], channels[1], channels[0]}, &img8)
+			for _, ch := range channels {
+				ch.Close()
+			}
+		}
+	}
+
+	ok := gocv.IMWrite(fjpg, img8)
 	if !ok {
 		err = fmt.Errorf("error saving %s", fjpg)
 		return err