/// <summary>
/// AN EXPERIMENTAL SPECTROGRAM - A FALSE-COLOR VERSION OF A standard scale SPECTROGRAM.
/// </summary>
/// <param name="dbSpectrogramData">The original data for decibel spectrogram.</param>
/// <param name="nrSpectrogram">The noise-reduced spectrogram.</param>
/// <param name="sourceRecordingName">Name of the source file. Required only to add label to spectrogram.</param>
/// <returns>Image of spectrogram.</returns>
public static Image <Rgb24> GetDecibelSpectrogram_Ridges(
double[,] dbSpectrogramData,
SpectrogramStandard nrSpectrogram,
string sourceRecordingName)
{
// ########################### SOBEL ridge detection
var ridgeThreshold = 3.5;
var matrix = ImageTools.WienerFilter(dbSpectrogramData, 3);
var hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
// ########################### EIGEN ridge detection
//double ridgeThreshold = 6.0;
//double dominanceThreshold = 0.7;
//var rotatedData = MatrixTools.MatrixRotate90Anticlockwise(dbSpectrogramData);
//byte[,] hits = RidgeDetection.StructureTensorRidgeDetection(rotatedData, ridgeThreshold, dominanceThreshold);
//hits = MatrixTools.MatrixRotate90Clockwise(hits);
// ########################### EIGEN ridge detection
var frameStep = nrSpectrogram.Configuration.WindowStep;
var sampleRate = nrSpectrogram.SampleRate;
var image = SpectrogramTools.CreateFalseColourDecibelSpectrogram(dbSpectrogramData, nrSpectrogram.Data, hits);
image = BaseSonogram.GetImageAnnotatedWithLinearHertzScale(
image,
sampleRate,
frameStep,
$"AN EXPERIMENTAL DECIBEL SPECTROGRAM with ridges ({sourceRecordingName})",
ImageTags[Experimental]);
//var image = decibelSpectrogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM - with ridges");
return(image);
}
/// <summary>
/// A FALSE-COLOUR VERSION OF DECIBEL SPECTROGRAM
/// Taken and adapted from Spectrogram Image 5 in the method of CLASS Audio2InputForConvCNN.cs:.
/// </summary>
/// <param name="dbSpectrogramData">the sonogram data (NOT noise reduced). </param>
public static Image <Rgb24> DrawStandardSpectrogramInFalseColour(double[,] dbSpectrogramData)
{
// Do NOISE REDUCTION
double noiseReductionParameter = 2.0;
var tuple = SNR.NoiseReduce(dbSpectrogramData, NoiseReductionType.Standard, noiseReductionParameter);
double[,] nrSpectrogramData = tuple.Item1; // store data matrix
double ridgeThreshold = 2.5;
double[,] matrix = dbSpectrogramData;
byte[,] hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
// ################### RESEARCH QUESTION:
// I tried different EXPERIMENTS IN NORMALISATION
//double min; double max;
//DataTools.MinMax(spectralSelection, out min, out max);
//double range = max - min;
// readjust min and max to create the effect of contrast stretching. It enhances the spectrogram a bit
//double fractionalStretching = 0.2;
//min = min + (range * fractionalStretching);
//max = max - (range * fractionalStretching);
//range = max - min;
// ULTIMATELY THE BEST APPROACH APPEARED TO BE FIXED NORMALISATION BOUNDS
double truncateMin = -95.0;
double truncateMax = -30.0;
double filterCoefficient = 0.75;
double[,] dbSpectrogramNorm = SpectrogramTools.NormaliseSpectrogramMatrix(dbSpectrogramData, truncateMin, truncateMax, filterCoefficient);
truncateMin = 0;
truncateMax = 50;
// nr = noise reduced
double[,] nrSpectrogramNorm = SpectrogramTools.NormaliseSpectrogramMatrix(nrSpectrogramData, truncateMin, truncateMax, filterCoefficient);
nrSpectrogramNorm = MatrixTools.BoundMatrix(nrSpectrogramNorm, 0.0, 0.9);
nrSpectrogramNorm = MatrixTools.SquareRootOfValues(nrSpectrogramNorm);
nrSpectrogramNorm = DataTools.normalise(nrSpectrogramNorm);
// create image from normalised data
var image = SpectrogramTools.CreateFalseColourDecibelSpectrogramForZooming(dbSpectrogramNorm, nrSpectrogramNorm, hits);
return(image);
}
public static AudioToSonogramResult GenerateFourSpectrogramImages(
FileInfo sourceRecording,
FileInfo path2SoxSpectrogram,
Dictionary <string, string> configDict,
bool dataOnly = false,
bool makeSoxSonogram = false)
{
var result = new AudioToSonogramResult();
if (dataOnly && makeSoxSonogram)
{
throw new ArgumentException("Can't produce data only for a SoX sonogram");
}
if (makeSoxSonogram)
{
SpectrogramTools.MakeSonogramWithSox(sourceRecording, configDict, path2SoxSpectrogram);
result.Path2SoxImage = path2SoxSpectrogram;
}
else if (dataOnly)
{
var recordingSegment = new AudioRecording(sourceRecording.FullName);
var sonoConfig = new SonogramConfig(configDict); // default values config
// disable noise removal
sonoConfig.NoiseReductionType = NoiseReductionType.None;
Log.Warn("Noise removal disabled!");
var sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
result.DecibelSpectrogram = sonogram;
}
else
{
// init the image stack
var list = new List <Image>();
// IMAGE 1) draw amplitude spectrogram
var recordingSegment = new AudioRecording(sourceRecording.FullName);
var sonoConfig = new SonogramConfig(configDict); // default values config
// disable noise removal for first two spectrograms
var disabledNoiseReductionType = sonoConfig.NoiseReductionType;
sonoConfig.NoiseReductionType = NoiseReductionType.None;
BaseSonogram sonogram = new AmplitudeSonogram(sonoConfig, recordingSegment.WavReader);
// remove the DC bin if it has not already been removed.
// Assume test of divisible by 2 is good enough.
int binCount = sonogram.Data.GetLength(1);
if (!binCount.IsEven())
{
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.FrameCount - 1, binCount - 1);
}
//save spectrogram data at this point - prior to noise reduction
var spectrogramDataBeforeNoiseReduction = sonogram.Data;
const double neighbourhoodSeconds = 0.25;
int neighbourhoodFrames = (int)(sonogram.FramesPerSecond * neighbourhoodSeconds);
const double lcnContrastLevel = 0.001;
LoggedConsole.WriteLine("LCN: FramesPerSecond (Prior to LCN) = {0}", sonogram.FramesPerSecond);
LoggedConsole.WriteLine("LCN: Neighbourhood of {0} seconds = {1} frames", neighbourhoodSeconds, neighbourhoodFrames);
const int lowPercentile = 20;
sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLowestPercentileSubtraction(sonogram.Data, lowPercentile);
sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLCNDivision(sonogram.Data, neighbourhoodFrames, lcnContrastLevel);
//sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_byLowestPercentileSubtraction(sonogram.Data, lowPercentile);
var image = sonogram.GetImageFullyAnnotated("AMPLITUDE SPECTROGRAM + Bin LCN (Local Contrast Normalisation)");
list.Add(image);
//string path2 = @"C:\SensorNetworks\Output\Sonograms\dataInput2.png";
//Histogram.DrawDistributionsAndSaveImage(sonogram.Data, path2);
// double[,] matrix = sonogram.Data;
double[,] matrix = ImageTools.WienerFilter(sonogram.Data, 3);
double ridgeThreshold = 0.25;
byte[,] hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
hits = RidgeDetection.JoinDisconnectedRidgesInMatrix(hits, matrix, ridgeThreshold);
image = SpectrogramTools.CreateFalseColourAmplitudeSpectrogram(spectrogramDataBeforeNoiseReduction, null, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "AMPLITUDE SPECTROGRAM + LCN + ridge detection");
list.Add(image);
Image envelopeImage = ImageTrack.DrawWaveEnvelopeTrack(recordingSegment, image.Width);
list.Add(envelopeImage);
// IMAGE 2) now draw the standard decibel spectrogram
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
result.DecibelSpectrogram = (SpectrogramStandard)sonogram;
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM");
list.Add(image);
Image segmentationImage = ImageTrack.DrawSegmentationTrack(
sonogram,
EndpointDetectionConfiguration.K1Threshold,
EndpointDetectionConfiguration.K2Threshold,
image.Width);
list.Add(segmentationImage);
// keep the sonogram data for later use
double[,] dbSpectrogramData = (double[, ])sonogram.Data.Clone();
// 3) now draw the noise reduced decibel spectrogram
// #NOISE REDUCTION PARAMETERS - restore noise reduction ##################################################################
sonoConfig.NoiseReductionType = disabledNoiseReductionType;
sonoConfig.NoiseReductionParameter = double.Parse(configDict[AnalysisKeys.NoiseBgThreshold] ?? "2.0");
// #NOISE REDUCTION PARAMETERS - MARINE HACK ##################################################################
//sonoConfig.NoiseReductionType = NoiseReductionType.FIXED_DYNAMIC_RANGE;
//sonoConfig.NoiseReductionParameter = 80.0;
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM + Lamel noise subtraction");
list.Add(image);
// keep the sonogram data for later use
double[,] nrSpectrogramData = sonogram.Data;
// 4) A FALSE-COLOUR VERSION OF SPECTROGRAM
// ########################### SOBEL ridge detection
ridgeThreshold = 3.5;
matrix = ImageTools.WienerFilter(dbSpectrogramData, 3);
hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
// ########################### EIGEN ridge detection
//double ridgeThreshold = 6.0;
//double dominanceThreshold = 0.7;
//var rotatedData = MatrixTools.MatrixRotate90Anticlockwise(dbSpectrogramData);
//byte[,] hits = RidgeDetection.StructureTensorRidgeDetection(rotatedData, ridgeThreshold, dominanceThreshold);
//hits = MatrixTools.MatrixRotate90Clockwise(hits);
// ########################### EIGEN ridge detection
image = SpectrogramTools.CreateFalseColourDecibelSpectrogram(dbSpectrogramData, nrSpectrogramData, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "DECIBEL SPECTROGRAM - Colour annotated");
list.Add(image);
// 5) TODO: ONE OF THESE YEARS FIX UP THE CEPTRAL SONOGRAM
////SpectrogramCepstral cepgram = new SpectrogramCepstral((AmplitudeSonogram)amplitudeSpg);
////var mti3 = SpectrogramTools.Sonogram2MultiTrackImage(sonogram, configDict);
////var image3 = mti3.GetImage();
////image3.Save(fiImage.FullName + "3", ImageFormat.Png);
// 6) COMBINE THE SPECTROGRAM IMAGES
result.CompositeImage = ImageTools.CombineImagesVertically(list);
}
return(result);
}
public static AudioToSonogramResult GenerateSpectrogramImages(FileInfo sourceRecording, Dictionary <string, string> configDict, DirectoryInfo outputDirectory)
{
// the source name was set up in the Analyse() method. But it could also be obtained directly from recording.
string sourceName = configDict[ConfigKeys.Recording.Key_RecordingFileName];
sourceName = Path.GetFileNameWithoutExtension(sourceName);
var result = new AudioToSonogramResult();
// init the image stack
var list = new List <Image>();
// 1) draw amplitude spectrogram
var recordingSegment = new AudioRecording(sourceRecording.FullName);
// default values config except disable noise removal for first two spectrograms
SonogramConfig sonoConfig = new SonogramConfig(configDict)
{
NoiseReductionType = NoiseReductionType.None
};
BaseSonogram sonogram = new AmplitudeSonogram(sonoConfig, recordingSegment.WavReader);
// remove the DC bin
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.FrameCount - 1, sonogram.Configuration.FreqBinCount);
// save spectrogram data at this point - prior to noise reduction
double[,] spectrogramDataBeforeNoiseReduction = sonogram.Data;
const int lowPercentile = 20;
const double neighbourhoodSeconds = 0.25;
int neighbourhoodFrames = (int)(sonogram.FramesPerSecond * neighbourhoodSeconds);
const double lcnContrastLevel = 0.25;
////LoggedConsole.WriteLine("LCN: FramesPerSecond (Prior to LCN) = {0}", sonogram.FramesPerSecond);
////LoggedConsole.WriteLine("LCN: Neighbourhood of {0} seconds = {1} frames", neighbourhoodSeconds, neighbourhoodFrames);
sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_ShortRecordings_SubtractAndLCN(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
// draw amplitude spectrogram unannotated
FileInfo outputImage1 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".amplitd.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage1.FullName);
// draw amplitude spectrogram annotated
var image = sonogram.GetImageFullyAnnotated("AMPLITUDE SPECTROGRAM + Bin LCN (Local Contrast Normalisation)");
list.Add(image);
////string path2 = @"C:\SensorNetworks\Output\Sonograms\dataInput2.png";
////Histogram.DrawDistributionsAndSaveImage(sonogram.Data, path2);
// 2) A FALSE-COLOUR VERSION OF AMPLITUDE SPECTROGRAM
double ridgeThreshold = 0.20;
double[,] matrix = ImageTools.WienerFilter(sonogram.Data, 3);
byte[,] hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
hits = RidgeDetection.JoinDisconnectedRidgesInMatrix(hits, matrix, ridgeThreshold);
image = SpectrogramTools.CreateFalseColourAmplitudeSpectrogram(spectrogramDataBeforeNoiseReduction, null, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "AMPLITUDE SPECTROGRAM + LCN + ridge detection");
list.Add(image);
Image envelopeImage = ImageTrack.DrawWaveEnvelopeTrack(recordingSegment, image.Width);
list.Add(envelopeImage);
// 3) now draw the standard decibel spectrogram
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
// remove the DC bin
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.FrameCount - 1, sonogram.Configuration.FreqBinCount);
// draw decibel spectrogram unannotated
FileInfo outputImage2 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".deciBel.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage2.FullName);
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM");
list.Add(image);
Image segmentationImage = ImageTrack.DrawSegmentationTrack(
sonogram,
EndpointDetectionConfiguration.K1Threshold,
EndpointDetectionConfiguration.K2Threshold,
image.Width);
list.Add(segmentationImage);
// keep the sonogram data (NOT noise reduced) for later use
double[,] dbSpectrogramData = (double[, ])sonogram.Data.Clone();
// 4) now draw the noise reduced decibel spectrogram
sonoConfig.NoiseReductionType = NoiseReductionType.Standard;
sonoConfig.NoiseReductionParameter = 3;
////sonoConfig.NoiseReductionType = NoiseReductionType.SHORT_RECORDING;
////sonoConfig.NoiseReductionParameter = 50;
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
// draw decibel spectrogram unannotated
FileInfo outputImage3 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".noNoise_dB.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage3.FullName);
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM + Lamel noise subtraction");
list.Add(image);
// keep the sonogram data for later use
double[,] nrSpectrogramData = sonogram.Data;
// 5) A FALSE-COLOUR VERSION OF DECIBEL SPECTROGRAM
ridgeThreshold = 2.5;
matrix = ImageTools.WienerFilter(dbSpectrogramData, 3);
hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
image = SpectrogramTools.CreateFalseColourDecibelSpectrogram(dbSpectrogramData, nrSpectrogramData, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "DECIBEL SPECTROGRAM - Colour annotated");
list.Add(image);
// 6) COMBINE THE SPECTROGRAM IMAGES
Image compositeImage = ImageTools.CombineImagesVertically(list);
FileInfo outputImage = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".5spectro.png"));
compositeImage.Save(outputImage.FullName, ImageFormat.Png);
result.SpectrogramFile = outputImage;
// 7) Generate the FREQUENCY x OSCILLATIONS Graphs and csv data
////bool saveData = true;
////bool saveImage = true;
////double[] oscillationsSpectrum = Oscillations2014.GenerateOscillationDataAndImages(sourceRecording, configDict, saveData, saveImage);
return(result);
}