使用gamma校正提升jpg亮度

cmd/proc.go

@@ -8,7 +8,7 @@ import (
 	"github.com/airbusgeo/godal"
 	"github.com/sirupsen/logrus"
 	"github.com/spf13/cobra"
-	producer "starwiz.cn/sjy01/image-proc/producer"
+	producer "starwiz.cn/sjy01/image-proc/pkg/producer"
 )
 
 var (

pkg/config/config.go

@@ -0,0 +1,8 @@
+package config
+
+type CoRegistrationConfig struct {
+	CRBlockNW        int    `yaml:"cr_block_nw" mapstructure:"cr_block_nw"`
+	CRBlockNH        int    `yaml:"cr_block_nh" mapstructure:"cr_block_nh"`
+	CRResampleMethod string `yaml:"cr_resample_method" mapstructure:"cr_resample_method"`
+	FUSBandOrder     string `yaml:"fu_band_order" mapstructure:"fu_band_order"`
+}

pkg/producer/gdal_pansharpen.go

@@ -4,6 +4,7 @@ import (
 	"image"
 	"os"
 	"os/exec"
+	"path/filepath"
 	"strings"
 
 	log "github.com/sirupsen/logrus"
@@ -83,7 +84,8 @@ func PansharpenIHS(panImage, mssImage gocv.Mat) gocv.Mat {
 }
 
 func GDALPansharpen(panTiff, mssTiff string) (string, error) {
-	fusedTIff := strings.Replace(mssTiff, "MSS", "FUS", 1)
+	fusedTIff := strings.Replace(mssTiff, "MSS", "FUS", -1)
+	os.MkdirAll(filepath.Dir(fusedTIff), 0755)
 	// pansharpenCmd := exec.Command("gdal_pansharpen.py", "-w 0.6 -w 0.1 -w 0.3 -w 0 -b 3 -b 2 -b 1", panTiff, mssTiff, fusedTIff, "-r cubic", "-of GTiff")
 	pansharpenCmd := exec.Command("gdal_pansharpen.py",
 		"-w", "0.4", "-w", "0.2", "-w", "0.4", "-w", "0",

pkg/producer/image_proc_test.go

@@ -18,22 +18,22 @@ func TestGDALPansharpen(t *testing.T) {
 
 func TestGTiffToJPG(t *testing.T) {
 	godal.RegisterAll()
-	tiff := "../data/051622/006/SJY01_MSS_20240516_101236_051622_096_006.tiff"
-	jpg := "../data/051622/006/SJY01_MSS_20240516_101236_051622_096_006.jpg"
+	tiff := "../data/051622/006/MSS/SJY01_MSS_20240516_101236_051622_096_006.tiff"
+	jpg := "../data/051622/006/MSS/SJY01_MSS_20240516_101236_051622_096_006.jpg"
 	err := GTiffToJPG(tiff, jpg, false)
 	if err != nil {
 		t.Error(err)
 	}
 
-	// tiff = "../data/051622/006/SJY01_PAN_20240516_101236_051622_096_006.tiff"
-	// jpg = "../data/051622/006/SJY01_PAN_20240516_101236_051622_096_006.jpg"
-	// err = GTiffToJPG(tiff, jpg, false)
-	// if err != nil {
-	// 	t.Error(err)
-	// }
+	tiff = "../data/051622/006/PAN/SJY01_PAN_20240516_101236_051622_096_006.tiff"
+	jpg = "../data/051622/006/PAN/SJY01_PAN_20240516_101236_051622_096_006.jpg"
+	err = GTiffToJPG(tiff, jpg, false)
+	if err != nil {
+		t.Error(err)
+	}
 
-	tiff = "../data/051622/006/SJY01_FUS_20240516_101236_051622_096_006.tiff"
-	jpg = "../data/051622/006/SJY01_FUS_20240516_101236_051622_096_006.jpg"
+	tiff = "../data/051622/006/FUS/SJY01_FUS_20240516_101236_051622_096_006.tiff"
+	jpg = "../data/051622/006/FUS/SJY01_FUS_20240516_101236_051622_096_006.jpg"
 	err = GTiffToJPG(tiff, jpg, true)
 	if err != nil {
 		t.Error(err)

pkg/producer/jpg.go

@@ -0,0 +1,150 @@
+package imageproc
+
+import (
+	"fmt"
+	"image"
+	"math"
+
+	"github.com/airbusgeo/godal"
+	log "github.com/sirupsen/logrus"
+	"gocv.io/x/gocv"
+)
+
+func GTiffToJPG(ftiff, fjpg string, reversed bool) error {
+	// 打开 TIFF 文件
+	ds, err := godal.Open(ftiff)
+	if err != nil {
+		log.Printf("Error opening TIFF file %s: %v", ftiff, err)
+		return err
+	}
+	defer ds.Close()
+
+	bands := ds.Bands()
+	log.Infof("creating JPG for TIFF file %s.", ftiff)
+
+	// 获取图像大小
+	width := bands[0].Structure().SizeX
+	height := bands[0].Structure().SizeY
+	bandsCnt := len(bands)
+
+	// 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 {
+			fmt.Printf("Error reading band %d: %v\n", i, err)
+			return err
+		}
+
+		// 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*bandsCnt+i, int16(value))
+			}
+		}
+	}
+
+	channels := gocv.Split(img)
+	for i, ch := range channels {
+		// 2. 计算图像的最小值和最大值
+		minVal, maxVal, minLoc, maxLoc := gocv.MinMaxLoc(ch)
+		log.Printf("Min value: %f, Max value: %f, min location: %v, max location: %v", minVal, maxVal, minLoc, maxLoc)
+
+		// 3. 将16位图像线性拉伸到8位图像
+		scale := 255.0 / (maxVal - minVal)
+		shift := -minVal * scale
+		ch.ConvertToWithParams(&channels[i], gocv.MatTypeCV8U, scale, shift)
+	}
+
+	img8bit := gocv.NewMat()
+	defer img8bit.Close()
+	if reversed {
+		gocv.Merge([]gocv.Mat{channels[2], channels[1], channels[0]}, &img8bit)
+	} else {
+		gocv.Merge(channels, &img8bit)
+	}
+
+	for i := range channels {
+		channels[i].Close()
+	}
+
+	gocv.Resize(img8bit, &img8bit,
+		image.Point{X: img8bit.Cols() / 2, Y: img8bit.Rows() / 2},
+		0, 0, gocv.InterpolationCubic)
+
+	// 7. 应用伽玛校正提升亮度
+	// avgBrightness := calculateAverageBrightness(img8bit)
+	// gamma := determineGammaValue(avgBrightness)
+	// log.Printf("Average Brightness: %f, Determined Gamma: %f", avgBrightness, gamma)
+
+	gammaCorrected := applyGammaCorrection(img8bit, 1.6) // 伽玛值
+	defer gammaCorrected.Close()
+	ok := gocv.IMWriteWithParams(fjpg, gammaCorrected, []int{gocv.IMWriteJpegOptimize, 1})
+	if !ok {
+		err = fmt.Errorf("error saving %s", fjpg)
+		return err
+	}
+
+	// gocv.IMWrite(strings.Replace(fjpg, ".jpg", "_8.jpg", 1), img8bit)
+
+	return nil
+}
+
+// applyGammaCorrection applies gamma correction to the image
+func applyGammaCorrection(src gocv.Mat, gamma float64) gocv.Mat {
+	lookupTable := make([]uint8, 256)
+	invGamma := 1.0 / gamma
+	for i := 0; i < 256; i++ {
+		lookupTable[i] = uint8(math.Pow(float64(i)/255.0, invGamma) * 255.0)
+	}
+
+	dst := gocv.NewMat()
+	gammaMat, err := gocv.NewMatFromBytes(1, 256, gocv.MatTypeCV8UC1, lookupTable)
+	if err != nil {
+		log.Printf("Error creating gamma correction matrix: %v", err)
+		return src
+	}
+	defer gammaMat.Close()
+
+	gocv.LUT(src, gammaMat, &dst)
+	return dst
+}
+
+// calculateAverageBrightness calculates the average brightness of the image
+func calculateAverageBrightness(img gocv.Mat) float64 {
+	if img.Channels() == 1 {
+		return img.Mean().Val1
+	}
+	gray := gocv.NewMat()
+	defer gray.Close()
+	gocv.CvtColor(img, &gray, gocv.ColorBGRToGray)
+	return gray.Mean().Val1
+	// mean := gocv.NewMat()
+	// dstStdDev := gocv.NewMat()
+	// defer mean.Close()
+	// defer dstStdDev.Close()
+	// gocv.MeanStdDev(gray, &mean, &dstStdDev)
+	// return float64(mean.GetFloatAt(0, 0))
+}
+
+// determineGammaValue determines an appropriate gamma value based on the average brightness
+func determineGammaValue(avgBrightness float64) float64 {
+	targetBrightness := 180.0
+	if avgBrightness < 0.1 {
+		return 1.0
+	}
+	gamma := math.Log(targetBrightness/255.0) / math.Log(avgBrightness/255.0)
+	return gamma
+}

pkg/producer/scenes.go

@@ -88,7 +88,7 @@ func (r *Registrator) SubScenes() (panScenes []*Scene, mssScenes []*Scene, err e
 
 func (r *Registrator) SaveScenesToTiff(panScenes []*Scene, mssScenes []*Scene) error {
 	for i, scene := range panScenes {
-		dir := filepath.Join(r.Params.OutputDir, fmt.Sprintf("%03d", i+1))
+		dir := filepath.Join(r.Params.OutputDir, fmt.Sprintf("%03d", i+1), "PAN")
 		os.MkdirAll(dir, 0755)
 
 		tiff := filepath.Base(r.Params.PanTiffFile)
@@ -105,7 +105,7 @@ func (r *Registrator) SaveScenesToTiff(panScenes []*Scene, mssScenes []*Scene) e
 	}
 
 	for i, scene := range mssScenes {
-		dir := filepath.Join(r.Params.OutputDir, fmt.Sprintf("%03d", i+1))
+		dir := filepath.Join(r.Params.OutputDir, fmt.Sprintf("%03d", i+1), "MSS")
 		os.MkdirAll(dir, 0755)
 
 		tiff := filepath.Base(r.Params.MssTiffFile)

producer/jpg.go

@@ -1,84 +0,0 @@
-package imageproc
-
-import (
-	"fmt"
-	"image"
-
-	"github.com/airbusgeo/godal"
-	log "github.com/sirupsen/logrus"
-	"gocv.io/x/gocv"
-)
-
-func GTiffToJPG(ftiff, fjpg string, reversed bool) error {
-	// 打开 TIFF 文件
-	ds, err := godal.Open(ftiff)
-	if err != nil {
-		log.Printf("Error opening TIFF file %s: %v", ftiff, err)
-		return err
-	}
-	defer ds.Close()
-
-	bands := ds.Bands()
-	log.Infof("creating JPG for TIFF file %s.", ftiff)
-
-	// 获取图像大小
-	width := bands[0].Structure().SizeX
-	height := bands[0].Structure().SizeY
-	bandsCnt := len(bands)
-
-	// 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 {
-			fmt.Printf("Error reading band %d: %v\n", i, err)
-			return err
-		}
-
-		// 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*bandsCnt+i, int16(value))
-			}
-		}
-	}
-
-	// 重采样图像
-	gocv.Resize(img, &img, image.Point{X: img.Cols() / 2, Y: img.Rows() / 2}, 0, 0, gocv.InterpolationCubic)
-
-	// 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*1.5, 0)
-	} else {
-		img.ConvertToWithParams(&img8, gocv.MatTypeCV8UC3, 1.0/256.0*1.5, 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
-	}
-
-	return nil
-}