321 lines
8.8 KiB
Go
321 lines
8.8 KiB
Go
package main
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import (
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"bufio"
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"fmt"
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"image"
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"math"
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"os"
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"github.com/chai2010/tiff"
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log "github.com/sirupsen/logrus"
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"gocv.io/x/gocv"
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)
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type Registrate interface{}
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const (
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MssBands = 4
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PixelBytes = 2
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PanWidth = 9344 // 像素宽度
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MssWidth = 2336
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BlockNH = 5
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BlockNW = 10
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DownSampled ResampleMethod = "down_sample_pan"
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UpSampled ResampleMethod = "up_sample_mss"
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)
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type ResampleMethod string
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type Registrator struct {
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PanImage gocv.Mat
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PanHeight int
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PanWidth int
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MssImages [4]gocv.Mat
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MssHeight int
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MssWidth int
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phaseShifts [4][]*PhaseShiftM
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registeredImages [4]gocv.Mat
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rgbirImage gocv.Mat
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resampleMethod ResampleMethod
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}
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func NewRegistrator() *Registrator {
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var r Registrator
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return &r
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}
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func (r *Registrator) LoadPanRaw(raw string) error {
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data, err := os.ReadFile(raw)
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if err != nil {
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log.Error("Error reading raw file: ", err)
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return err
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}
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height := len(data) / (PanWidth * PixelBytes)
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r.PanImage, err = gocv.NewMatFromBytes(height, PanWidth, gocv.MatTypeCV16U, data)
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if err != nil {
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log.Error("Error creating Mat from bytes: ", err)
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return err
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}
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r.PanHeight = height
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r.PanWidth = PanWidth
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return nil
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}
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func (r *Registrator) LoadMssRaw(raw string) error {
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data, err := os.ReadFile(raw)
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if err != nil {
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log.Error("Error reading raw file: ", err)
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return err
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}
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height := len(data) / (MssWidth * PixelBytes * MssBands)
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mssData := make([][]byte, MssBands)
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for h := 0; h < height; h++ {
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row := data[h*MssWidth*MssBands*PixelBytes : (h+1)*MssWidth*MssBands*PixelBytes]
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for i := 0; i < MssBands; i++ {
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mssData[i] = append(mssData[i], row[i*MssWidth*PixelBytes:(i+1)*MssWidth*PixelBytes]...)
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}
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}
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for i := 0; i < MssBands; i++ {
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r.MssImages[i], err = gocv.NewMatFromBytes(height, MssWidth, gocv.MatTypeCV16U, mssData[i])
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if err != nil {
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log.Error("Error creating Mat from bytes: ", err)
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return err
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}
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}
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r.MssHeight = height
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r.MssWidth = MssWidth
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return nil
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}
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// 将PAN降采样后计算相位相关的偏移量
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func (r *Registrator) DoDownPhaseCorrelation() error {
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// 确保 MSS 高度是 PAN 高度的 1/4
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if r.MssHeight*4 != r.PanHeight {
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err := fmt.Errorf("MSS height is not 1/4 of PAN height, invalid raw file")
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log.Error(err)
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return err
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}
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// 将PAN将采样作为轮廓匹配基准图像
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downsampledPanImage := gocv.NewMat()
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gocv.Resize(r.PanImage, &downsampledPanImage,
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image.Point{X: r.MssWidth, Y: r.MssHeight}, 0, 0, gocv.InterpolationLinear)
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// 对每个 MSS 波段图像进行上采样
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// upsampledMSSImages := make([]gocv.Mat, MssBands)
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for i := 0; i < MssBands; i++ {
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// upsampledMSSImages[i] = gocv.NewMat()
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// gocv.Resize(r.MssImages[i], &upsampledMSSImages[i],
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// image.Point{X: r.PanWidth, Y: r.PanHeight}, 0, 0, gocv.InterpolationLinear)
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// r.msToRaw(upsampledMSSImages[i].ToBytes(), fmt.Sprintf("MSS%d.RAW", i+1))
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}
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fmt.Println("down sampled PAN images size:", downsampledPanImage.Size())
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// 分块高度
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blockHeight := r.MssHeight / BlockNH
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alignedMssData := make([][]byte, MssBands)
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for band := 0; band < MssBands; band++ {
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alignedMSSImage := gocv.NewMatWithSize(r.MssHeight, r.MssWidth, gocv.MatTypeCV16U)
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for bh := 0; bh < BlockNH; bh++ {
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// 读取 PAN 和 MSS 分块数据
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y1 := (bh + 1) * blockHeight
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if bh == BlockNH-1 {
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y1 = r.MssHeight
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}
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var shiftM PhaseShiftM
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shiftM.Block.width = r.MssWidth // 块宽度
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shiftM.Block.height = y1 - bh*blockHeight // 块高度
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shiftM.Block.coord.X = 0 // 块左上角x坐标
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shiftM.Block.coord.Y = bh * blockHeight // 块左上角y坐标
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rect := image.Rect(
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shiftM.Block.coord.X, shiftM.Block.coord.Y,
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shiftM.Block.coord.X+shiftM.Block.width, shiftM.Block.coord.Y+shiftM.Block.height,
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)
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log.Println("Band", band+1, ", processing block", bh, rect)
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panBlock := downsampledPanImage.Region(rect)
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mssBlock := r.MssImages[band].Region(rect)
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// 处理每个分块
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alignedBlock, phaseShift := r.processBlock(panBlock, mssBlock)
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shiftM.dx = phaseShift.X
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shiftM.dy = phaseShift.Y
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r.phaseShifts[band] = append(r.phaseShifts[band], &shiftM)
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// alignedBlockData := alignedBlock.ToBytes()
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// alignedMssData[band] = append(alignedMssData[band], alignedBlockData...)
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// if alignedMSSImage.Empty() {
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// alignedMSSImage = alignedBlock.Clone()
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// } else {
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// gocv.Vconcat(alignedMSSImage, alignedBlock, &alignedMSSImage)
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// alignedBlock.Close()
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// }
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panBlock.Close()
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mssBlock.Close()
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alignedBlock.Close()
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}
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r.registeredImages[band] = alignedMSSImage
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}
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// 使用平均偏移量来做平移变换
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for band := 0; band < MssBands; band++ {
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var efficientShiftM int
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var xTotal, yTotal float32
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for _, shift := range r.phaseShifts[band] {
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if math.IsNaN(float64(shift.dx)) || math.IsNaN(float64(shift.dy)) {
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continue
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}
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efficientShiftM += 1
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xTotal += shift.dx
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yTotal += shift.dy
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}
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dx := xTotal / float32(efficientShiftM)
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dy := yTotal / float32(efficientShiftM)
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log.Println("Band", band+1, "average shift:", dx, dy, "efficientShiftM:", efficientShiftM)
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translationMat := gocv.NewMatWithSize(2, 3, gocv.MatTypeCV32F)
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translationMat.SetFloatAt(0, 0, 1)
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translationMat.SetFloatAt(0, 1, 0)
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translationMat.SetFloatAt(0, 2, dx)
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translationMat.SetFloatAt(1, 0, 0)
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translationMat.SetFloatAt(1, 1, 1)
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translationMat.SetFloatAt(1, 2, dy)
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alignedMss := gocv.NewMatWithSize(r.MssHeight, r.MssWidth, gocv.MatTypeCV32FC1)
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cvtMss := gocv.NewMat()
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r.MssImages[band].ConvertTo(&cvtMss, gocv.MatTypeCV32FC1)
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// 手动平移像素
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outY := math.MaxInt
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for y := 0; y < r.MssHeight; y++ {
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for x := 0; x < r.MssWidth; x++ {
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// 计算新的坐标
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newX := x + int(dx)
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newY := y + int(dy)
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// 如果新坐标在图像范围内，进行像素值赋值
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if newX >= 0 && newX < r.MssWidth && newY >= 0 && newY < r.MssHeight {
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alignedMss.SetFloatAt(y, x, cvtMss.GetFloatAt(newY, newX))
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} else {
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// 如果新坐标不在图像范围内，设置为黑色
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alignedMss.SetFloatAt(y, x, 0)
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if outY > y {
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outY = y
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log.Println("Warning: pixel out of range", x, y)
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}
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}
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}
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}
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// gocv.WarpAffine(cvtMss, &alignedMss, translationMat, image.Pt(cvtMss.Size()[1], cvtMss.Size()[0]))
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alignedMss.ConvertTo(&alignedMss, gocv.MatTypeCV16U)
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alignedMssData[band] = append(alignedMssData[band], alignedMss.ToBytes()...)
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translationMat.Close()
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cvtMss.Close()
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alignedMss.Close()
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}
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r.mssToRaw(alignedMssData)
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return nil
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}
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func (r *Registrator) panToTiff(panImage gocv.Mat, filePath string) error {
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return nil
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}
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func (r *Registrator) mssToTiff(registeredImages [4]gocv.Mat, filePath string) error {
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// 创建合并后的图像（RGBIR）
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rgbirImage := gocv.NewMatWithSize(r.PanHeight, r.PanWidth, gocv.MatTypeCV16UC4) // 4通道，16位
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for y := 0; y < r.PanHeight; y++ {
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for x := 0; x < r.PanWidth; x++ {
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r := registeredImages[0].GetShortAt(y, x)
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g := registeredImages[1].GetShortAt(y, x)
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b := registeredImages[2].GetShortAt(y, x)
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ir := registeredImages[3].GetShortAt(y, x)
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rgbirImage.SetShortAt(y, x*4+0, r)
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rgbirImage.SetShortAt(y, x*4+1, g)
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rgbirImage.SetShortAt(y, x*4+2, b)
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rgbirImage.SetShortAt(y, x*4+3, ir)
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}
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}
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// 将合并后的图像保存为TIFF文件
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fileName := "data/registered_rgbir.tiff"
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tiffFile, err := os.Create(fileName)
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if err != nil {
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fmt.Println("Error creating TIFF file:", err)
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return err
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}
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defer tiffFile.Close()
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// 使用tiff库保存图像
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img, err := rgbirImage.ToImage()
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if err != nil {
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fmt.Println("Error converting Mat to image:", err)
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return err
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}
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if err := tiff.Encode(tiffFile, img, nil); err != nil {
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fmt.Println("Error encoding TIFF file:", err)
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return err
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}
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fmt.Println("Saved", fileName)
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return nil
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}
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func (r *Registrator) mssToRaw(mssData [][]byte) error {
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f, err := os.OpenFile("data/downsampled_registered_mss.RAW", os.O_CREATE|os.O_TRUNC|os.O_WRONLY, 0777)
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if err != nil {
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return err
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}
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log.Println("Writing downsampled registered MSS to RAW file...", len(mssData[0])*4)
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log.Println("width:", r.MssWidth*PixelBytes*4)
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log.Println("height:", r.MssHeight)
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w := bufio.NewWriter(f)
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for row := 0; row < r.MssHeight; row++ {
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w.Write(mssData[0][row*r.MssWidth*PixelBytes : (row+1)*r.MssWidth*PixelBytes])
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w.Write(mssData[1][row*r.MssWidth*PixelBytes : (row+1)*r.MssWidth*PixelBytes])
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w.Write(mssData[2][row*r.MssWidth*PixelBytes : (row+1)*r.MssWidth*PixelBytes])
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w.Write(mssData[3][row*r.MssWidth*PixelBytes : (row+1)*r.MssWidth*PixelBytes])
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}
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return nil
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}
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func (r *Registrator) bytesToRaw(mssData []byte, filePath string) error {
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f, err := os.OpenFile(filePath, os.O_CREATE|os.O_TRUNC|os.O_WRONLY, 0777)
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if err != nil {
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return err
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}
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w := bufio.NewWriter(f)
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w.Write(mssData)
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return nil
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}
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