pansharpen

filter.go

@@ -0,0 +1,78 @@
+package imageproc
+
+import (
+	"image"
+	"math"
+
+	log "github.com/sirupsen/logrus"
+
+	"gocv.io/x/gocv"
+)
+
+func PANFilter(panImage16UC1 gocv.Mat) gocv.Mat {
+	log.Println("Applying PAN filter...")
+	// 转换为浮点数类型进行傅里叶变换
+	imgFloat := gocv.NewMat()
+	panImage16UC1.ConvertTo(&imgFloat, gocv.MatTypeCV32F)
+
+	// 使用傅里叶变换
+	planes := gocv.NewMat()
+	gocv.Merge([]gocv.Mat{imgFloat, gocv.NewMatWithSize(imgFloat.Rows(), imgFloat.Cols(), gocv.MatTypeCV32F)}, &planes)
+	dft := gocv.NewMat()
+	gocv.DFT(planes, &dft, gocv.DftComplexOutput)
+
+	// 转换DFT图像，使低频分量位于中心
+	dftShifted := shiftDFT(dft)
+
+	// 创建掩膜
+	rows, cols := panImage16UC1.Rows(), panImage16UC1.Cols()
+	crow, ccol := rows/2, cols/2
+	mask := gocv.NewMatWithSize(rows, cols, gocv.MatTypeCV32FC2)
+	mask.SetTo(gocv.NewScalar(1.0, 1.0, 0.0, 0.0))
+
+	r := 30 // 调整这个参数来改变滤波效果
+	for i := 0; i < rows; i++ {
+		for j := 0; j < cols; j++ {
+			if math.Abs(float64(i-crow)) <= float64(r) && math.Abs(float64(j-ccol)) <= float64(r) {
+				mask.SetFloatAt(i, j*2, 0)
+				mask.SetFloatAt(i, j*2+1, 0)
+			}
+		}
+	}
+
+	// 应用掩膜并进行反向DFT
+	filtered := gocv.NewMat()
+	gocv.MulSpectrums(dftShifted, mask, &filtered, 0)
+	filteredShifted := shiftDFT(filtered)
+	idft := gocv.NewMat()
+	gocv.DFT(filteredShifted, &idft, gocv.DftInverse|gocv.DftRealOutput)
+
+	// 标准化图像到0-65535范围
+	gocv.Normalize(idft, &idft, 0, 65535, gocv.NormMinMax)
+	idft.ConvertTo(&idft, gocv.MatTypeCV16U)
+
+	return idft
+}
+
+// shiftDFT 将DFT结果进行频谱平移
+func shiftDFT(src gocv.Mat) gocv.Mat {
+	rows, cols := src.Rows(), src.Cols()
+	crow, ccol := rows/2, cols/2
+
+	q0 := src.Region(image.Rect(0, 0, ccol, crow))
+	q1 := src.Region(image.Rect(ccol, 0, cols, crow))
+	q2 := src.Region(image.Rect(0, crow, ccol, rows))
+	q3 := src.Region(image.Rect(ccol, crow, cols, rows))
+
+	tmp := gocv.NewMatWithSize(crow, ccol, src.Type())
+
+	q0.CopyTo(&tmp)
+	q3.CopyTo(&q0)
+	tmp.CopyTo(&q3)
+
+	q1.CopyTo(&tmp)
+	q2.CopyTo(&q1)
+	tmp.CopyTo(&q2)
+
+	return src
+}