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分景后配准

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This commit is contained in:
nuknal
2024-11-01 09:19:42 +08:00
parent e51d07901d
commit 75e4dd6d90
7 changed files with 191 additions and 58 deletions
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8
cmd/proc.go
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@@ -7,6 +7,7 @@ import (
"strings"
"github.com/airbusgeo/godal"
"github.com/duke-git/lancet/v2/mathutil"
"github.com/sirupsen/logrus"
"github.com/spf13/cobra"
"starwiz.cn/sjy01/image-proc/pkg/calculator"
@@ -78,7 +79,7 @@ var procCmd = &cobra.Command{
processor.DoMomentMatching()
}
if err := processor.DoPhaseCorrelation(); err != nil {
if err := processor.DoPhaseCorrelation(true); err != nil {
logrus.Fatal(err)
}
@@ -96,6 +97,11 @@ var procCmd = &cobra.Command{
logrus.Error(err)
}
scenesCnt := mathutil.Min(len(panScenes), len(mssScenes))
for i := 0; i < scenesCnt; i++ {
processor.RegisterScenes(panScenes[i], mssScenes[i])
}
processor.OutputL1A(panScenes, mssScenes)
producer.CleanScenes(panScenes)
producer.CleanScenes(mssScenes)

7
cmd/test.go
View File

@@ -31,12 +31,13 @@ var testCmd = &cobra.Command{
// out := producer.CV_Sobel(mv[i])
// utils.SavePanToGDALGTiff(out, 0, 0, "data/temp/out_"+strconv.Itoa(i)+".tif", 1.3)
// }
for i := 1; i < len(mv); i++ {
mv[i] = producer.CV_ECCAlign(mv[0], mv[i])
index := len(mv) - 1
for i := index - 1; i >= 0; i-- {
mv[i] = producer.CV_ECCAlign(mv[index], mv[i])
}
out := gocv.NewMat()
mv[0].ConvertTo(&mv[0], gocv.MatTypeCV16U)
mv[index].ConvertTo(&mv[index], gocv.MatTypeCV16U)
gocv.Merge(mv, &out)
utils.SaveBGRToGDALGTiff(out, 4, 0, 0, 5.2,
[]godal.ColorInterp{godal.CIBlue, godal.CIGreen, godal.CIRed, godal.CIUndefined},

9
pkg/producer/ecc_align.go
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@@ -10,6 +10,7 @@ import (
// align the image via Enhanced Correlation Coefficient (ECC) algorithm
func CV_ECCAlign(templateImage, inputImage gocv.Mat) gocv.Mat {
retMatType := templateImage.Type()
warpMode := gocv.MotionHomography
var warpMatrix gocv.Mat
switch warpMode {
@@ -27,7 +28,7 @@ func CV_ECCAlign(templateImage, inputImage gocv.Mat) gocv.Mat {
var mask = gocv.NewMat()
templateImage.ConvertTo(&templateImage, gocv.MatTypeCV32FC1)
inputImage.ConvertTo(&inputImage, gocv.MatTypeCV32FC1)
log.Info("cv::findTransformECC...")
retval := gocv.FindTransformECC(templateImage, inputImage, &warpMatrix, warpMode, criteria, mask, 5)
log.Info("cv::findTransformECC ret:", retval)
@@ -39,9 +40,9 @@ func CV_ECCAlign(templateImage, inputImage gocv.Mat) gocv.Mat {
gocv.WarpAffine(inputImage, &aligned, warpMatrix, sz)
}
aligned.ConvertTo(&aligned, gocv.MatTypeCV16U)
templateImage.ConvertTo(&templateImage, gocv.MatTypeCV16U)
inputImage.ConvertTo(&inputImage, gocv.MatTypeCV16U)
aligned.ConvertTo(&aligned, retMatType)
templateImage.ConvertTo(&templateImage, retMatType)
inputImage.ConvertTo(&inputImage, retMatType)
return aligned
}

18
pkg/producer/edge_phase_correlation.go
View File

@@ -1,8 +1,6 @@
package producer
import (
"fmt"
"gocv.io/x/gocv"
)
@@ -14,30 +12,30 @@ import (
// SKIP: 多光谱各个波段的边缘检测结果不佳
func CV_Canny(img0 gocv.Mat) gocv.Mat {
fmt.Println(img0.Cols(), img0.Rows(), img0.Type().String())
dst8 := gocv.NewMatWithSize(img0.Rows(), img0.Cols(), gocv.MatTypeCV8U)
defer dst8.Close()
gocv.Normalize(img0, &dst8, 0, 255, gocv.NormMinMax)
dst8.ConvertTo(&dst8, gocv.MatTypeCV8U)
dstEdge := gocv.NewMat()
gocv.Canny(dst8, &dstEdge, 10, 100)
dstEdge.ConvertTo(&dstEdge, gocv.MatTypeCV16U)
dstEdge.ConvertTo(&dstEdge, img0.Type())
return dstEdge
}
func CV_Sobel(img0 gocv.Mat) gocv.Mat {
matType := img0.Type()
// x 方向
sobelX := gocv.NewMat()
gocv.Sobel(img0, &sobelX, gocv.MatTypeCV32F, 1, 0, 5, 1.5, 0, gocv.BorderDefault)
sobelX.ConvertTo(&sobelX, gocv.MatTypeCV16U)
gocv.Sobel(img0, &sobelX, gocv.MatTypeCV32FC1, 1, 0, 5, 1.5, 0, gocv.BorderDefault)
sobelX.ConvertTo(&sobelX, matType)
// y 方向
sobelY := gocv.NewMat()
gocv.Sobel(img0, &sobelY, gocv.MatTypeCV32F, 0, 1, 5, 1.5, 0, gocv.BorderIsolated)
sobelY.ConvertTo(&sobelY, gocv.MatTypeCV16U)
gocv.Sobel(img0, &sobelY, gocv.MatTypeCV32FC1, 0, 1, 5, 1.5, 0, gocv.BorderIsolated)
sobelY.ConvertTo(&sobelY, matType)
// 合并
sobelXY := gocv.NewMat()
gocv.Sobel(img0, &sobelXY, gocv.MatTypeCV32F, 1, 1, 5, 1.5, 0, gocv.BorderDefault)
sobelXY.ConvertTo(&sobelXY, gocv.MatTypeCV16U)
gocv.Sobel(img0, &sobelXY, gocv.MatTypeCV32FC1, 1, 1, 5, 1.5, 0, gocv.BorderDefault)
sobelXY.ConvertTo(&sobelXY, matType)
return sobelY
}

91
pkg/producer/image_registration.go
View File

@@ -22,8 +22,6 @@ const (
PixelBytes = 2
PanWidth = payload.PAN_PIXEL_WIDTH // 像素宽度
MssWidth = payload.MSS_PIXEL_WIDTH
BlockNH = 8
BlockNW = 4
OverlappedBlockLines = 1000 // 重叠块的行数
DownSampled ResampleMethod = "down_sample_pan"
UpSampled ResampleMethod = "up_sample_mss"
@@ -33,6 +31,7 @@ const (
ReferenceShiftYB2 = 200.0
ReferenceShiftYB3 = 300.0
ReferenceShiftYB4 = 400.0
MaxShiftY = 480
)
type ResampleMethod string
@@ -47,6 +46,8 @@ type ImgProc struct {
MssImages [4]gocv.Mat
MssHeight int
MssWidth int
blockH int
blockW int
shiftMutex sync.Mutex
phaseShifts [4][]PhaseShiftM
@@ -72,6 +73,8 @@ type ImgProc struct {
func NewImgProc(rsmethod ResampleMethod) *ImgProc {
var r ImgProc
r.resampleMethod = rsmethod
r.blockH = 8
r.blockW = 8
return &r
}
@@ -141,7 +144,14 @@ func (r *ImgProc) LoadMssRaw() error {
return nil
}
func (r *ImgProc) DoPhaseCorrelation() error {
func (r *ImgProc) DoPhaseCorrelation(skip bool) error {
if skip {
for i := 0; i < MssBands; i++ {
r.registeredMssImages[i] = r.MssImages[i].Clone()
}
return nil
}
switch r.resampleMethod {
case UpSampled:
return r.CalcUpPhaseCorrelation()
@@ -167,11 +177,13 @@ func (r *ImgProc) CalcDownPhaseCorrelation() error {
log.Println("down sampled PAN images size:", downsampledPanImage.Size())
// 分块高度
blockHeight := r.MssHeight / BlockNH
blockWidth := r.MssWidth / BlockNW
blockHeight := r.MssHeight / r.blockH
blockWidth := r.MssWidth / r.blockW
log.Infof("blockHeight=%d, blockWidth=%d", blockHeight, blockWidth)
// 在 MSS 4 个波段上进行配准
err := r.doPhaseCorrelation(r.MssImages[0],
err := r.doPhaseCorrelation(downsampledPanImage,
[]gocv.Mat{r.MssImages[0], r.MssImages[1], r.MssImages[2], r.MssImages[3]},
r.MssHeight, r.MssWidth, blockHeight, blockWidth)
if err != nil {
@@ -195,22 +207,30 @@ func (r *ImgProc) CalcDownPhaseCorrelation() error {
// r.DoMSSCoRegistration(true)
// 基于 PAN 图像进行配准
err = r.doPhaseCorrelation(downsampledPanImage,
[]gocv.Mat{r.registeredMssImages[0]},
r.MssHeight, r.MssWidth, blockHeight, blockWidth)
if err != nil {
return err
// err = r.doPhaseCorrelation(downsampledPanImage,
// []gocv.Mat{r.registeredMssImages[0]},
// r.MssHeight, r.MssWidth, blockHeight, blockWidth)
// if err != nil {
// return err
// }
// r.fileterPhaseShift([]float64{30.0}, true)
// r.calcMSSDeltaCoeffs(1)
// r.DoPANCoRegistration()
// 裁掉位移部分
r.MssHeight -= MaxShiftY
r.PanHeight -= MaxShiftY * 4
r.PanImage = r.PanImage.Region(image.Rect(0, 0, r.PanWidth, r.PanHeight))
for i := 0; i < MssBands; i++ {
r.registeredMssImages[i] = r.registeredMssImages[i].Region(image.Rect(0, 0, r.MssWidth, r.MssHeight))
}
r.fileterPhaseShift([]float64{30.0}, true)
r.calcMSSDeltaCoeffs(1)
r.DoPANCoRegistration()
return nil
}
// 将MSS升采样采样后计算相位相关的偏移量
func (r *ImgProc) CalcUpPhaseCorrelation() error {
log.Fatal("unsuppotted up-resample method")
log.Fatal("not implemented yet")
// 确保 MSS 高度是 PAN 高度的 1/4
if r.MssHeight*4 != r.PanHeight {
err := fmt.Errorf("MSS height is not 1/4 of PAN height, invalid raw file")
@@ -219,34 +239,36 @@ func (r *ImgProc) CalcUpPhaseCorrelation() error {
}
// 在 MSS 4 个波段上进行配准
err := r.doPhaseCorrelation(r.MssImages[0],
[]gocv.Mat{r.MssImages[0], r.MssImages[1], r.MssImages[2], r.MssImages[3]},
r.MssHeight, r.MssWidth, r.MssHeight/BlockNH, r.MssWidth/BlockNW)
if err != nil {
return err
}
r.DoMSSCoRegistration(false)
// err := r.doPhaseCorrelation(r.MssImages[0],
// []gocv.Mat{r.MssImages[0], r.MssImages[1], r.MssImages[2], r.MssImages[3]},
// r.MssHeight, r.MssWidth, r.MssHeight/r.blockH, r.MssWidth/r.blockW)
// if err != nil {
// return err
// }
// r.DoMSSCoRegistration(false)
upsampledMssImages := make([]gocv.Mat, MssBands)
for i := 0; i < MssBands; i++ {
upsampledMssImages[i] = gocv.NewMat()
gocv.Resize(r.registeredMssImages[i], &upsampledMssImages[i],
gocv.Resize(r.MssImages[i], &upsampledMssImages[i],
image.Point{X: r.PanWidth, Y: r.PanHeight}, 0, 0, gocv.InterpolationCubic)
}
fmt.Println("up sampled MSS images size:", upsampledMssImages[0].Size())
// 分块高度 - BlockNH, BlockNW % 4 == 0
blockHeight := r.PanHeight / BlockNH
blockWidth := r.PanWidth / BlockNW
blockHeight := r.PanHeight / r.blockH
blockWidth := r.PanWidth / r.blockW
log.Infof("blockHeight=%d, blockWidth=%d", blockHeight, blockWidth)
// 基于 PAN 图像进行配准
r.doPhaseCorrelation(r.PanImage,
[]gocv.Mat{upsampledMssImages[0]},
r.MssHeight, r.MssWidth, blockHeight, blockWidth)
return r.DoPANCoRegistration()
r.doPhaseCorrelation(r.PanImage, upsampledMssImages,
r.PanHeight, r.PanWidth, blockHeight, blockWidth)
r.fileterPhaseShift([]float64{64, 64, 64, 64}, true)
r.calcMSSDeltaCoeffs(4)
r.DoMSSCoRegistration(false)
return nil
}
func (r *ImgProc) doPhaseCorrelation(base gocv.Mat,
@@ -261,8 +283,8 @@ func (r *ImgProc) doPhaseCorrelation(base gocv.Mat,
r.deltaYCoeffs[band] = make([]float64, 0)
}
for bh := 0; bh < BlockNH; bh++ {
for bw := 0; bw < BlockNW; bw++ {
for bh := 0; bh < r.blockH; bh++ {
for bw := 0; bw < r.blockW; bw++ {
wg.Add(1)
go func(bh, bw int) {
defer wg.Done()
@@ -449,10 +471,6 @@ func (r *ImgProc) DoMSSCoRegistration(byEdge bool) error {
mapY.Close()
}
// 裁掉末尾的的 MSS 480 行 和 PAN 的 480*4 行
r.PanHeight -= 360 * 4
r.MssHeight -= 360
return nil
}
@@ -498,9 +516,6 @@ func (r *ImgProc) DoPANCoRegistration() error {
r.registeredMssImages[i].Close()
r.registeredMssImages[i] = registeredMSS
}
// 裁掉末尾的的 MSS 480 行 和 PAN 的 480*4 行
r.PanHeight -= 120 * 4
r.MssHeight -= 120
return nil
}

80
pkg/producer/phase_correlation.go
View File

@@ -3,8 +3,10 @@ package producer
import (
"errors"
"image"
"math/cmplx"
"github.com/duke-git/lancet/v2/slice"
"github.com/mjibson/go-dsp/fft"
log "github.com/sirupsen/logrus"
"gocv.io/x/gocv"
)
@@ -31,9 +33,9 @@ func CV_PhaseCorrelate(panBlock, mssBlock gocv.Mat) (gocv.Point2f, float64) {
mssBlock.ConvertTo(&mss, gocv.MatTypeCV32FC1)
defer mss.Close()
hann := gocv.NewMat()
hann := gocv.NewMatWithSize(pan.Rows(), pan.Cols(), pan.Type())
defer hann.Close()
gocv.CreateHanningWindow(&hann, image.Point{X: pan.Cols(), Y: pan.Rows()}, pan.Type())
shift, response := gocv.PhaseCorrelate(pan, mss, hann)
dx := shift.X
@@ -64,3 +66,77 @@ func (r *ImgProc) fileterPhaseShift(thredholds []float64, greaterThan bool) erro
return nil
}
func PhaseCorrelate(panBlock, mssBlock gocv.Mat) (gocv.Point2f, float64) {
// 计算傅里叶变换
panFreqDomain, _, _, err := toFreqDomain(panBlock)
if err != nil {
log.Error(err)
}
mssFreqDomain, width, height, err := toFreqDomain(mssBlock)
if err != nil {
log.Error(err)
}
// 计算共轭乘积并积累相位信息
crossPowerSpectrum := make([][]complex128, height)
for i := range crossPowerSpectrum {
crossPowerSpectrum[i] = make([]complex128, width)
}
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
if panFreqDomain[y][x] != 0 && mssFreqDomain[y][x] != 0 {
crossPowerSpectrum[y][x] = panFreqDomain[y][x] * cmplx.Conj(mssFreqDomain[y][x])
}
}
}
// 归一化
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
if crossPowerSpectrum[y][x] != 0 {
magnitude := cmplx.Abs(crossPowerSpectrum[y][x])
crossPowerSpectrum[y][x] = crossPowerSpectrum[y][x] / complex(magnitude, 0)
}
}
}
ifftResult := fft.IFFT2(crossPowerSpectrum)
// 查找最大值及其对应的平移参数
maxVal := 0.0
var dx, dy float64
for y := 0; y < height; y++ {
for x := 0; x < width; x++ {
val := real(ifftResult[y][x])
if val > maxVal {
maxVal = val
dx = float64(x)
dy = float64(y)
}
}
}
log.Debugf("Block shift: dx = %f, dy = %f. response = %f", dx, dy, 0.0)
return gocv.Point2f{X: float32(dx), Y: float32(dy)}, 0.0
}
func toFreqDomain(input gocv.Mat) ([][]complex128, int, int, error) {
height := input.Rows()
width := input.Cols()
data := make([][]complex128, height)
for y := 0; y < height; y++ {
data[y] = make([]complex128, width)
for x := 0; x < width; x++ {
grayColor := float64(uint16(input.GetShortAt(y, x)))
data[y][x] = complex(grayColor, 0)
}
}
freqDomain := fft.FFT2(data)
return freqDomain, width, height, nil
}

36
pkg/producer/scene_register.go Normal file
View File

@@ -0,0 +1,36 @@
package producer
import (
"github.com/sirupsen/logrus"
"gocv.io/x/gocv"
)
// 分景后再做配准
func (r *ImgProc) RegisterScenes(pan, mss *Scene) error {
proc := NewImgProc(DownSampled)
proc.PanImage = pan.Mat[0]
proc.MssImages = [4]gocv.Mat{mss.Mat[0], mss.Mat[1], mss.Mat[2], mss.Mat[3]}
proc.MssHeight = mss.Height
proc.MssWidth = mss.Width
proc.PanHeight = pan.Height
proc.PanWidth = pan.Width
err := proc.DoPhaseCorrelation(false)
if err != nil {
logrus.Error("register scene failed: ", err)
return err
}
pan.Height = proc.PanHeight
pan.Width = proc.PanWidth
pan.Mat[0] = proc.PanImage
mss.Height = proc.MssHeight
mss.Width = proc.MssWidth
for i := 0; i < 4; i++ {
mss.Mat[i].Close()
mss.Mat[i] = proc.registeredMssImages[i]
}
return nil
}