相邻列均衡算法（张兵，2006）

pkg/rrc/moment_matching.go

@@ -7,8 +7,7 @@ import (
 	"gocv.io/x/gocv"
 )
 
-// Destriping multisensor imagery with moment matching
-
+// Destriping multisensor imagery with moment matching [Gadallah, 2000]
 func DoMomentMatching(originalImg gocv.Mat) {
 	probes := originalImg.Cols()
 	log.Printf("do moment matching for %d probes", probes)
@@ -54,3 +53,42 @@ func DoMomentMatching(originalImg gocv.Mat) {
 		}
 	}
 }
+
+// 相邻列均衡算法（张兵，2006）- 实测结果不如上面的矩匹配算法
+func DoMomentMatching2006(originalImg gocv.Mat) {
+	probes := originalImg.Cols()
+	log.Printf("do moment matching for %d probes", probes)
+	// 第i个探元的像元均值和标准差
+	means := make([]float64, probes)
+	stds := make([]float64, probes)
+	// 计算每个探元的均值和标准差
+	for x := 0; x < originalImg.Cols(); x++ {
+		var total int64
+		n := originalImg.Rows()
+		var dn uint16
+		for y := 0; y < n; y++ {
+			dn = uint16(originalImg.GetShortAt(y, x))
+			total += int64(dn)
+		}
+		means[x] = float64(total) / float64(n)
+
+		var a float64
+		for y := 0; y < n; y++ {
+			dn = uint16(originalImg.GetShortAt(y, x))
+			a += math.Pow(float64(dn)-means[x], 2)
+		}
+		stds[x] = math.Sqrt(a / float64(n))
+	}
+
+	// 修正 DN_adjusted[i] = (DN[i] - means[i]) *sig/stds[i]+mu
+	for x := 1; x < originalImg.Cols()-1; x++ {
+		// 列参考值和列参考标准差
+		mu := (means[x-1] + means[x+1]/2 + means[x]) / 2
+		sig := (stds[x-1] + stds[x+1]/2 + stds[x]) / 2
+		for y := 0; y < originalImg.Rows(); y++ {
+			dn := uint16(originalImg.GetShortAt(y, x))
+			dn_adjusted := uint16((float64(dn)-means[x])*sig/stds[x] + mu)
+			originalImg.SetShortAt(y, x, int16(dn_adjusted))
+		}
+	}
+}