Files
sjy01-image-proc/pkg/rrc/rrc.go
2024-06-21 12:47:14 +08:00

200 lines
4.0 KiB
Go

package rrc
import (
"bufio"
"fmt"
"os"
"path/filepath"
"runtime"
"sync"
log "github.com/sirupsen/logrus"
"gocv.io/x/gocv"
"starwiz.cn/sjy01/image-proc/pkg/utils"
)
// 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 // 16bit像素值
)
type RRC struct {
LUTOutDir string
Histograms [5]ProbeHistogram
}
func NewRRC(dir string) *RRC {
r := RRC{LUTOutDir: dir}
r.Histograms[0].init(PANCameraProbeNum)
for i := 1; i < 5; i++ {
r.Histograms[i].init(MSSCameraProbeNum)
}
os.MkdirAll(r.LUTOutDir, 0755)
return &r
}
func (rrc *RRC) Statistical(dsPAN, dsMSS string) error {
rrc.StatisticalPAN(dsPAN)
rrc.StatisticalMSS(dsMSS)
return nil
}
func (rrc *RRC) Close() {}
// 统计探元灰度的累积概率密度
func (rrc *RRC) StatisticalPAN(dsfile string) error {
utils.PrintMemStats()
f, err := os.Open(dsfile)
if err != nil {
return err
}
defer f.Close()
scanner := bufio.NewScanner(f)
var files []string
for scanner.Scan() {
files = append(files, scanner.Text())
}
// 并发处理
var wg sync.WaitGroup
jobs := make(chan struct{}, 5)
var mutex sync.Mutex
for _, file := range files {
wg.Add(1)
go func(l0 string) {
defer wg.Done()
jobs <- struct{}{}
defer func() { <-jobs }()
log.Println("statistical PAN RAW: ", l0)
data, err := os.ReadFile(l0)
if err != nil {
log.Error("Error reading file: ", err)
return
}
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
}
var hist ProbeHistogram
hist.init0(PANCameraProbeNum)
hist.statistical(img)
img.Close()
mutex.Lock()
log.Println("sum PAN histogram...")
rrc.Histograms[0].sum([]*ProbeHistogram{&hist})
hist.free()
runtime.GC()
utils.PrintMemStats()
mutex.Unlock()
}(file)
}
wg.Wait()
log.Println("compute PAN histogram...")
rrc.Histograms[0].compute()
log.Println("save PAN gray table matrix.")
rrc.Histograms[0].saveLUT(filepath.Join(rrc.LUTOutDir, "B0.LUT"))
return nil
}
func (rrc *RRC) StatisticalMSS(dsfile string) error {
utils.PrintMemStats()
f, err := os.Open(dsfile)
if err != nil {
return err
}
defer f.Close()
scanner := bufio.NewScanner(f)
var files []string
for scanner.Scan() {
files = append(files, scanner.Text())
}
var wg sync.WaitGroup
jobs := make(chan struct{}, 5)
var mutex sync.Mutex
for _, file := range files {
wg.Add(1)
go func(l0 string) {
defer wg.Done()
jobs <- struct{}{}
defer func() { <-jobs }()
log.Println("statistical MSS RAW: ", l0)
data, err := os.ReadFile(l0)
if err != nil {
log.Error("Error reading file: ", err)
return
}
width := MSSCameraProbeNum
height := len(data) / (width * 4 * 2)
mssData := make([][]byte, 4)
for h := 0; h < height; h++ {
row := data[h*width*4*2 : (h+1)*width*4*2]
for i := 0; i < 4; i++ {
mssData[i] = append(mssData[i], row[i*width*2:(i+1)*width*2]...)
}
}
var mssImages [4]gocv.Mat
for i := 0; i < 4; i++ {
mssImages[i], err = gocv.NewMatFromBytes(height, width, gocv.MatTypeCV16U, mssData[i])
if err != nil {
log.Error("Error creating Mat from bytes: ", err)
return
}
var hist ProbeHistogram
hist.init0(MSSCameraProbeNum)
hist.statistical(mssImages[i])
mssImages[i].Close()
mutex.Lock()
log.Println("sum MSS histogram...")
rrc.Histograms[i+1].sum([]*ProbeHistogram{&hist})
hist.free()
runtime.GC()
utils.PrintMemStats()
mutex.Unlock()
}
}(file)
}
wg.Wait()
for i := 1; i < 5; i++ {
log.Println("compute MSS histogram...")
rrc.Histograms[i].compute()
log.Println("save MSS gray table matrix.")
rrc.Histograms[i].saveLUT(filepath.Join(rrc.LUTOutDir, fmt.Sprintf("B%d.LUT", i)))
}
return nil
}