public static Task <BitmapSource> Stretch(IRenderedImage image, double factor, double blackClipping)
{
return(Task.Run(async() => {
var imageStatistics = await image.RawImageData.Statistics.Task;
if (image.Image.Format == PixelFormats.Gray16)
{
using (var bmp = ImageUtility.BitmapFromSource(image.Image, System.Drawing.Imaging.PixelFormat.Format16bppGrayScale)) {
return Stretch(imageStatistics, bmp, image.Image.Format, factor, blackClipping);
}
}
else if (image.Image.Format == PixelFormats.Rgb48)
{
using (var bmp = ImageUtility.BitmapFromSource(image.Image, System.Drawing.Imaging.PixelFormat.Format48bppRgb)) {
return Stretch(imageStatistics, bmp, image.Image.Format, factor, blackClipping);
}
}
else
{
throw new NotSupportedException();
}
}));
}
public void MeasureContrast(IProgress <ApplicationStatus> progress)
{
try {
using (MyStopWatch.Measure()) {
Stopwatch overall = Stopwatch.StartNew();
progress?.Report(new ApplicationStatus()
{
Status = "Preparing image for contrast measurement"
});
_bitmapToAnalyze = ImageUtility.Convert16BppTo8Bpp(_originalBitmapSource);
_token.ThrowIfCancellationRequested();
//Crop if there is ROI
if (UseROI && InnerCropRatio < 1)
{
Rectangle cropRectangle = GetCropRectangle(InnerCropRatio);
_bitmapToAnalyze = new Crop(cropRectangle).Apply(_bitmapToAnalyze);
}
if (_noiseReduction == NoiseReductionEnum.Median)
{
new Median().ApplyInPlace(_bitmapToAnalyze);
}
//Make sure resizing is independent of Star Sensitivity
_resizefactor = (double)_maxWidth / _bitmapToAnalyze.Width;
_inverseResizefactor = 1.0 / _resizefactor;
/* Resize to speed up manipulation */
ResizeBitmapToAnalyze();
progress?.Report(new ApplicationStatus()
{
Status = "Measuring Contrast"
});
_token.ThrowIfCancellationRequested();
if (ContrastDetectionMethod == ContrastDetectionMethodEnum.Laplace)
{
if (_noiseReduction == NoiseReductionEnum.None || _noiseReduction == NoiseReductionEnum.Median)
{
int[,] kernel = new int[7, 7];
kernel = LaplacianOfGaussianKernel(7, 1.0);
new Convolution(kernel).ApplyInPlace(_bitmapToAnalyze);
}
else if (_noiseReduction == NoiseReductionEnum.Normal)
{
int[,] kernel = new int[9, 9];
kernel = LaplacianOfGaussianKernel(9, 1.4);
new Convolution(kernel).ApplyInPlace(_bitmapToAnalyze);
}
else if (_noiseReduction == NoiseReductionEnum.High)
{
int[,] kernel = new int[11, 11];
kernel = LaplacianOfGaussianKernel(11, 1.8);
new Convolution(kernel).ApplyInPlace(_bitmapToAnalyze);
}
else
{
int[,] kernel = new int[13, 13];
kernel = LaplacianOfGaussianKernel(13, 2.2);
new Convolution(kernel).ApplyInPlace(_bitmapToAnalyze);
}
//Get mean and standard dev
Accord.Imaging.ImageStatistics stats = new Accord.Imaging.ImageStatistics(_bitmapToAnalyze);
AverageContrast = stats.GrayWithoutBlack.Mean;
ContrastStdev = 0.01; //Stdev of convoluted image is not a measure of error - using same figure for all
}
else if (ContrastDetectionMethod == ContrastDetectionMethodEnum.Sobel)
{
if (_noiseReduction == NoiseReductionEnum.None || _noiseReduction == NoiseReductionEnum.Median)
{
//Nothing to do
}
else if (_noiseReduction == NoiseReductionEnum.Normal)
{
_bitmapToAnalyze = new FastGaussianBlur(_bitmapToAnalyze).Process(1);
}
else if (_noiseReduction == NoiseReductionEnum.High)
{
_bitmapToAnalyze = new FastGaussianBlur(_bitmapToAnalyze).Process(2);
}
else
{
_bitmapToAnalyze = new FastGaussianBlur(_bitmapToAnalyze).Process(3);
}
int[,] kernel =
{
{ -1, -2, 0, 2, 1 },
{ -2, -4, 0, 4, 2 },
{ 0, 0, 0, 0, 0 },
{ 2, 4, 0, -4, -2 },
{ 1, 2, 0, -2, -1 }
};
new Convolution(kernel).ApplyInPlace(_bitmapToAnalyze);
//Get mean and standard dev
Accord.Imaging.ImageStatistics stats = new Accord.Imaging.ImageStatistics(_bitmapToAnalyze);
AverageContrast = stats.GrayWithoutBlack.Mean;
ContrastStdev = 0.01; //Stdev of convoluted image is not a measure of error - using same figure for all
}
_token.ThrowIfCancellationRequested();
_bitmapToAnalyze.Dispose();
overall.Stop();
Debug.Print("Overall contrast detection: " + overall.Elapsed);
overall = null;
}
} catch (OperationCanceledException) {
} finally {
progress?.Report(new ApplicationStatus()
{
Status = string.Empty
});
}
return;
}
public void Detect(IProgress <ApplicationStatus> progress)
{
try {
using (MyStopWatch.Measure()) {
progress?.Report(new ApplicationStatus()
{
Status = "Preparing image for star detection"
});
_bitmapToAnalyze = ImageUtility.Convert16BppTo8Bpp(_originalBitmapSource);
_token.ThrowIfCancellationRequested();
/* Perform initial noise reduction on full size image if necessary */
if (_noiseReduction != NoiseReductionEnum.None)
{
ReduceNoise();
}
/* Resize to speed up manipulation */
ResizeBitmapToAnalyze();
/* prepare image for structure detection */
PrepareForStructureDetection(_bitmapToAnalyze);
progress?.Report(new ApplicationStatus()
{
Status = "Detecting structures"
});
/* get structure info */
_blobCounter = DetectStructures(_bitmapToAnalyze);
progress?.Report(new ApplicationStatus()
{
Status = "Analyzing stars"
});
_starlist = IdentifyStars();
_token.ThrowIfCancellationRequested();
if (_starlist.Count > 0)
{
var m = (from star in _starlist select star.HFR).Average();
var s = Math.Sqrt(((from star in _starlist select star.HFR * star.HFR).Sum() - _starlist.Count() * m * m) / _starlist.Count());
Logger.Info($"Average HFR: {m}, HFR σ: {s}, Detected Stars {_starlist.Count}");
//todo change
AverageHFR = m;
HFRStdDev = double.IsNaN(s) ? 0 : s;
DetectedStars = _starlist.Count;
}
_blobCounter = null;
_bitmapToAnalyze.Dispose();
}
} catch (OperationCanceledException) {
} finally {
progress?.Report(new ApplicationStatus()
{
Status = string.Empty
});
}
return;
}
public BahtinovImage GrabBahtinov()
{
var bahtinovImage = new BahtinovImage();
Bitmap convertedSource;
if (originalSource.Format != System.Windows.Media.PixelFormats.Gray8)
{
if (originalSource.Format != System.Windows.Media.PixelFormats.Gray16)
{
using (var imgToConvert = ImageUtility.BitmapFromSource(originalSource, System.Drawing.Imaging.PixelFormat.Format48bppRgb)) {
convertedSource = new Grayscale(0.2125, 0.7154, 0.0721).Apply(imgToConvert);
}
convertedSource = ImageUtility.Convert16BppTo8Bpp(ImageUtility.ConvertBitmap(convertedSource, System.Windows.Media.PixelFormats.Gray16));
}
else
{
convertedSource = ImageUtility.Convert16BppTo8Bpp(originalSource);
}
}
else
{
convertedSource = ImageUtility.BitmapFromSource(originalSource, System.Drawing.Imaging.PixelFormat.Format8bppIndexed);
convertedSource.Palette = ImageUtility.GetGrayScalePalette();
}
using (var focusEllipsePen = new System.Drawing.Pen(System.Drawing.Brushes.Green, 1)) {
using (var intersectEllipsePen = new System.Drawing.Pen(System.Drawing.Brushes.Red, 1)) {
var mediaColor = backgroundColor;
var drawingColor = System.Drawing.Color.FromArgb(mediaColor.A, mediaColor.R, mediaColor.G, mediaColor.B);
using (var linePen = new System.Drawing.Pen(drawingColor, 1)) {
using (var bahtinovedBitmap = new Bitmap(convertedSource.Width, convertedSource.Height, System.Drawing.Imaging.PixelFormat.Format24bppRgb)) {
Graphics graphics = Graphics.FromImage(bahtinovedBitmap);
graphics.DrawImage(convertedSource, 0, 0);
/* Apply filters and detection*/
CannyEdgeDetector filter = new CannyEdgeDetector();
filter.GaussianSize = 10;
filter.ApplyInPlace(convertedSource);
HoughLineTransformation lineTransform = new HoughLineTransformation();
lineTransform.ProcessImage(convertedSource);
HoughLine[] lines = lineTransform.GetMostIntensiveLines(6);
List <Line> bahtinovLines = new List <Line>();
foreach (HoughLine line in lines)
{
var k = TranslateHughLineToLine(line, bahtinovedBitmap.Width, bahtinovedBitmap.Height);
bahtinovLines.Add(k);
}
float x1, x2, y1, y2;
if (bahtinovLines.Count == 6)
{
var orderedPoints = bahtinovLines.OrderBy(x => 1.0d / x.Slope).ToList();
var threeLines = new List <Line>();
for (var i = 0; i < orderedPoints.Count(); i += 2)
{
var l1 = orderedPoints[i];
var l2 = orderedPoints[i + 1];
var inter = (l1.Intercept + l2.Intercept) / 2.0f;
var slope = (l1.Slope + l2.Slope) / 2.0f;
var centerLine = Line.FromSlopeIntercept(slope, inter);
threeLines.Add(centerLine);
x1 = 0;
x2 = convertedSource.Width;
y1 = double.IsInfinity(centerLine.Slope) ? centerLine.Intercept : centerLine.Slope + centerLine.Intercept;
y2 = double.IsInfinity(centerLine.Slope) ? centerLine.Intercept : (centerLine.Slope * (convertedSource.Width) + centerLine.Intercept);
graphics.DrawLine(
linePen,
new PointF(x1, y1),
new PointF(x2, y2));
}
/* Intersect outer bahtinov lines */
var intersection = threeLines[0].GetIntersectionWith(threeLines[2]);
if (intersection.HasValue)
{
/* get orthogonale to center line through intersection */
var centerBahtinovLine = threeLines[1];
var orthogonalSlope = -1.0f / centerBahtinovLine.Slope;
var orthogonalIntercept = intersection.Value.Y - orthogonalSlope * intersection.Value.X;
var orthogonalCenter = Line.FromSlopeIntercept(orthogonalSlope, orthogonalIntercept);
var intersection2 = centerBahtinovLine.GetIntersectionWith(orthogonalCenter);
if (intersection2.HasValue && !double.IsInfinity(intersection2.Value.X))
{
x1 = intersection.Value.X;
y1 = intersection.Value.Y;
x2 = intersection2.Value.X;
y2 = intersection2.Value.Y;
bahtinovImage.Distance = intersection.Value.DistanceTo(intersection2.Value);
var t = bahtinovImage.Distance * 4 / bahtinovImage.Distance;
var x3 = (float)((1 - t) * x1 + t * x2);
var y3 = (float)((1 - t) * y1 + t * y2);
var r = 10;
graphics.DrawEllipse(
intersectEllipsePen,
new RectangleF(x3 - r, y3 - r, 2 * r, 2 * r));
graphics.DrawEllipse(
focusEllipsePen,
new RectangleF(x2 - r, y2 - r, 2 * r, 2 * r));
graphics.DrawLine(
intersectEllipsePen,
new PointF(x3, y3),
new PointF(x2, y2));
}
}
}
var img = ImageUtility.ConvertBitmap(bahtinovedBitmap, System.Windows.Media.PixelFormats.Bgr24);
convertedSource.Dispose();
img.Freeze();
bahtinovImage.Image = img;
return(bahtinovImage);
}
}
}
}
}
