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RRC

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This commit is contained in:
nuknal
2024-06-13 20:33:42 +08:00
parent cd9a534458
commit 268076017e
7 changed files with 173 additions and 12 deletions
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18
pkg/calculator/camera.go
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@@ -7,15 +7,15 @@ import (
)
const (
FocalLength = 1300.0 // 焦距, mm
FOV = 1.7 // 对角线视场角,degree
FOVCALC = 1.86 // 对角线视场角,degree
PANPixels = 9344.0
PANCellSize = 3.2 // µm
MSSPixels = 2336.0
MSSCellSize = 12.8 // µm
AngleCamSatX = 0.0 // 相机与卫星本体X轴的安装角度, degree FIXME: 安装矩阵应该由卫星方提供
AngleCamSatY = 0.5 // 相机与卫星本体Y轴的安装角度, degree
FocalLength = 1300.0 // 焦距, mm
FOV = 1.7 // 对角线视场角,degree
FOVCALC = 1.86 // 对角线视场角,degree
PANPixels = 9344.0
PANCellSize = 3.2 // µm
MSSPixels = 2336.0
MSSCellSize = 12.8 // µm
CameraRoll = 0.0 // 相机与卫星本体X轴的安装角度, degree FIXME: 安装矩阵应该由卫星方提供
CameraPitch = 0.5 // 相机与卫星本体Y轴的安装角度, degree
)
// 计算过程使用PAN分辨率

4
pkg/calculator/intersection.go
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@@ -22,7 +22,7 @@ func IntersectionAttitude(q Quaternion, satPos84 []float64, satTime time.Time, u
direction := CameraDirectionVec(0, float64(ucam))
// -------- 相机坐标系下CCD成像方向向量转到卫星坐标系 --------
Rcam := CameraRotMatrix(AngleCamSatX*math.Pi/180.0, AngleCamSatY*math.Pi/180.0, 0)
Rcam := CameraRotMatrix(CameraRoll*math.Pi/180.0, CameraPitch*math.Pi/180.0, 0)
var dCam mat.VecDense
dCam.MulVec(Rcam, mat.NewVecDense(3, direction))
@@ -52,7 +52,7 @@ func IntersectionECI(Qsat2orbit, Qorbit2eci Quaternion, satPos84 []float64, satT
direction := []float64{0, math.Tan(alpha), -1.3} // 卫星（相机）坐标系下CCD成像方向向量
// -------- 相机坐标系下CCD成像方向向量转到卫星坐标系 --------
Rcam := CameraRotMatrix(AngleCamSatX*math.Pi/180.0, AngleCamSatY*math.Pi/180.0, 0)
Rcam := CameraRotMatrix(CameraRoll*math.Pi/180.0, CameraPitch*math.Pi/180.0, 0)
var dCam mat.VecDense
dCam.MulVec(Rcam, mat.NewVecDense(3, direction))

2
pkg/calculator/orbit.go
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@@ -37,7 +37,7 @@ func IntersectionECEF(Qsat2orbit Quaternion, satPos84, vec84 []float64, ucam int
direction := []float64{0, math.Tan(alpha), -1.3} // 卫星（相机）坐标系下CCD成像方向向量
// -------- 相机坐标系下CCD成像方向向量转到卫星坐标系 --------
Rcam := CameraRotMatrix(AngleCamSatX*math.Pi/180.0, AngleCamSatY*math.Pi/180.0, 0)
Rcam := CameraRotMatrix(CameraRoll*math.Pi/180.0, CameraPitch*math.Pi/180.0, 0)
var dCam mat.VecDense
dCam.MulVec(Rcam, mat.NewVecDense(3, direction))

18
pkg/producer/aux.go
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@@ -1,7 +1,10 @@
package producer
import (
"encoding/json"
"fmt"
"math"
"os"
"time"
log "github.com/sirupsen/logrus"
@@ -9,6 +12,7 @@ import (
"github.com/duke-git/lancet/v2/mathutil"
"github.com/paulmach/orb"
"github.com/paulmach/orb/geo"
"github.com/paulmach/orb/geojson"
"github.com/paulmach/orb/planar"
"starwiz.cn/sjy01/image-proc/pkg/auxilary"
"starwiz.cn/sjy01/image-proc/pkg/calculator"
@@ -20,6 +24,20 @@ func (r *Registrator) LoadAuxData() error {
return err
}
// 数据校验和测试
func (r *Registrator) AuxPrint() {
var fcPos84 geojson.FeatureCollection
for _, p := range r.AuxPlatforms {
lat, lon, _ := calculator.WGS84XYZtoLatLngH(p.W84PosX, p.W84PosY, p.W84PosZ)
point := orb.Point{lon, lat}
fcPos84.Features = append(fcPos84.Features, geojson.NewFeature(point))
}
data, _ := json.Marshal(fcPos84)
f, _ := os.Create(fmt.Sprintf("log/%s_aux_pos_84.geojson", r.Params.DataId))
defer f.Close()
f.Write(data)
}
func (r *Registrator) SceneImageTime(scene *Scene) (start, center, end time.Time) {
startPosInAux, endPosInAux := r.SceneInAuxIndex(scene)
centerPosInAux := (startPosInAux + endPosInAux) / 2

1
pkg/producer/params.go
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@@ -17,6 +17,7 @@ type Params struct {
FusTIffFile string
SubScenes bool
ReportFile string
DataId string
}
type XMLImageTask struct {

140
pkg/rrc/rrc.go Normal file
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@@ -0,0 +1,140 @@
package rrc
import (
"os"
log "github.com/sirupsen/logrus"
"gocv.io/x/gocv"
)
// Relative Radiation Correction
// 采用在轨统计定标方法。利用卫星在轨后获取的常规影像数据，统计每个探元出现的灰度频次。
const (
PANCameraProbeNum = 9344 // 全色探元数
MSSCameraProbeNum = 2336 // 多光谱探元数
MaxGrayLevel = 65536
)
type RRC struct {
PANDataSet []string
MSSDataSet []string
Histograms [5]BandHistogram
}
type BandHistogram struct {
width int // 探元数
N_i []int // N_i 探元像素总数 PAN 0-9343 MSS 0-2335
n_ik [][]int // n_ik 第i探元灰度等级为k的像素数统计 PAN 9343 x 65536 MSS 2335 x 65536
p_ik [][]float64 // p_ik = n_ik / N_i 探元灰度概率密度 PAN 9343 x 65536 MSS 2335 x 65536
m_l []int64 // 具有灰度等级l的像素总数 l = 0-65535
M int64 // 参与直方图统计的总像素数
P_l []float64 // P_l = m_l/M 所有探元的期望直方图灰度等级为l的概率密度
S_ik [][]float64 // S_ik = sum(p_ij),j=0..k 第i个探元直方图灰度等级k的累积概率密度
V_l []float64 // V_l = sum(P_j),j=0..l // 期望直方图灰度级l对应的累积概率密度
Tij [][]float64 // 第i个像元的j灰度等级对应的新的灰度值，用于修正图像
}
func (hist *BandHistogram) init(width int) {
hist.width = width
hist.M = 0
hist.N_i = make([]int, width)
hist.n_ik = make([][]int, width)
hist.p_ik = make([][]float64, width)
hist.m_l = make([]int64, MaxGrayLevel)
hist.P_l = make([]float64, MaxGrayLevel)
hist.S_ik = make([][]float64, width)
hist.V_l = make([]float64, MaxGrayLevel)
hist.Tij = make([][]float64, width)
for i := 0; i < width; i++ {
hist.n_ik[i] = make([]int, MaxGrayLevel)
hist.p_ik[i] = make([]float64, MaxGrayLevel)
hist.S_ik[i] = make([]float64, MaxGrayLevel)
hist.Tij[i] = make([]float64, MaxGrayLevel)
}
}
// 统计探元灰度的累积概率密度
func (rrc *RRC) StatisticalPAN(l0 string) error {
data, err := os.ReadFile(l0)
if err != nil {
return err
}
height := len(data) / (PANCameraProbeNum * 2)
img, err := gocv.NewMatFromBytes(height, PANCameraProbeNum, gocv.MatTypeCV16U, data)
if err != nil {
log.Error("Error creating Mat from bytes: ", err)
return err
}
hist := BandHistogram{}
hist.init(PANCameraProbeNum)
rrc.statistical(img, &hist)
rrc.compute(&hist)
rrc.output(&hist, "pan_gray_table.tif")
return nil
}
func (rrc *RRC) statistical(img gocv.Mat, hist *BandHistogram) error {
hist.M += int64(img.Rows() * img.Cols())
for i := 0; i < hist.width; i++ {
hist.N_i[i] += img.Rows()
}
for y := 0; y < img.Rows(); y++ {
for x := 0; x < img.Cols(); x++ {
gray := uint16(img.GetShortAt(x, y))
hist.n_ik[x][gray]++
}
}
for gray := 0; gray < MaxGrayLevel; gray++ {
for i := 0; i < hist.width; i++ {
hist.m_l[gray] += int64(hist.n_ik[i][gray])
}
}
return nil
}
func (rrc *RRC) compute(hist *BandHistogram) error {
width := len(hist.N_i)
for i := 0; i < width; i++ {
for k := 0; k < MaxGrayLevel; k++ {
hist.p_ik[i][k] = float64(hist.n_ik[i][k]) / float64(hist.N_i[i])
}
}
for gray := 0; gray < MaxGrayLevel; gray++ {
hist.P_l[gray] = float64(hist.m_l[gray]) / float64(hist.M)
}
for i := 0; i < width; i++ {
for k := 0; k < MaxGrayLevel; k++ {
hist.S_ik[i][k] = 0
for j := 0; j <= k; j++ {
hist.S_ik[i][k] += hist.p_ik[i][j]
}
}
}
for gray := 0; gray < MaxGrayLevel; gray++ {
hist.V_l[gray] = 0
for j := 0; j <= gray; j++ {
hist.V_l[gray] += hist.P_l[j]
}
}
return nil
}
func (rrc *RRC) output(hist *BandHistogram, referenceTIF string) error {
return nil
}