Exemple #1
0
        /// <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);
        }
Exemple #3
0
        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);
        }
Exemple #4
0
        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);
        }