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Advanced Digital Image Processing and Its Applications in Big Data

I: Concept and Background of Image Processing, Techniques, and Big Data: Introduction to Advanced Digital Image ProcessingIntroductionCategorization of Digital ImagesBinary ImageBlack and White Image-Bit Color FormatColor Format-Bit FormatPhases of Digital Image ProcessingAcquisition of an ImageImage EnhancementReferences: Different Techniques Used for Image ProcessingIntroductionAcquisition of an ImageImage Pre-ProcessingImage EnhancementImage AnalysisImage CompressionEdge DetectionSegmentationImage RepresentationReferences: Role and Support of Image Processing in Big DataIntroductionBig Data Mathematical Analysis TheoriesIndependent and Identical Distribution Theory (IID)Set TheoryCharacteristics of Big DataDifferent Techniques of Big Data AnalyticsEnsemble AnalysisAssociation AnalysisHigh-Dimensional AnalysisDeep AnalysisPrecision AnalysisDivide and Conquer AnalysisPerspective AnalysisSteps of Big Data ProcessingData CollectionData Storage and ManagementData Filtering and ExtractionData Cleaning and ValidationData AnalyticsData VisualizationImportance of Big Data in Image ProcessingHadoopParts of Hadoop ArchitectureHDFSMap ReduceWorking of HADOOP architectureImage Processing with Big Data AnalyticsImage preprocessingReferencesII: Advanced Image Processing Technical Phases for Big Data Analysis: Advanced Image Segmentation Techniques Used for Big DataIntroductionClassification of Image Segmentation TechniquesRegion-based SegmentationThreshold SegmentationRegional Growth SegmentationRegion Splitting and Merging MethodsEdge Detection SegmentationSobel OperatorLaplacian OperatorClustering-Based SegmentationHard ClusteringSoft ClusteringK-Means Clustering TechniqueFuzzy C-Means Clustering TechniqueSegmentation Based on Weakly Supervised Learning in CNNComparative Study of Image Segmentation TechniquesDiscussionReferences: Advance Object Detection and Clustering Techniques Used for Big DataIntroductionClusteringDifferences between Clustering and ClassificationDistance MeasureEuclidean DistanceMinkowski MetricManhattan MetricClustering AlgorithmsPartitioning-Based ClusteringK-Means ClusteringHierarchical ClusteringModel-Based ClusteringDensity-Based ClusteringFuzzy ClusteringGrid-Based ClusteringExclusive ClusteringOverlapping ClusteringOther Clustering MethodsReferences: Advanced Image Compression Techniques Used for Big DataIntroductionAn Overview of the Compression ProcessConcept of Image CompressionRelated work of Image Compression MethodsImage Compression TechniquesLossless CompressionLossy Compression TechniquesHybrid Compression TechniquesSome Advanced Image Compression TechniquesVector Quantization (VQ)Comparison of Various Compression AlgorithmsPerformance Parameters of Compression TechniquesPeak Signal-to-Noise RatioCompression RatioMean Square ErrorStructural Similarity IndexBits per PixelSignal-to-Noise RatioPercent Rate of DistortionCorrelation CoefficientStructural ContentApplications of Compression TechniquesSatellite ImagesBroadcast TelevisionGenetic ImagesInternet Telephony and TeleconferencingElectronic Health RecordsComputer CommunicationRemote Sensing via SatellitesReferencesIII: Various Application of Image Processing: Application of Image Processing and Data in Remote SensingIntroductionRemote SensingReferences: Application of Image Processing and Data Science in Medical ScienceIntroductionIdeal Dataset of Medical Imaging for Data AnalysisFundamentals of Medical Image ProcessingSteps of Image ProcessingProblems with Medical ImagesHeterogeneity of ImagesUnknown Delineation of ObjectsRobustness of AlgorithmsNoise Occurrence in ImageSpeckle NoiseCategories of Medical Image Data formationImage AcquisitionX-ray Medical ImagesTomography ImagesCT ImagesRadiography ImagesMRIUltrasound ImagesThermo Graphic ImagesMolecular Imaging or Nuclear MedicineImage DigitalizationQuantizationSpatial SamplingImage EnhancementHistogram TransformsPhase of RegistrationImage Data VisualizationImage Data analysisFeature ExtractionImage SegmentationImage ClassificationImage ManagementArchivingCommunicationRetrievalReferences: Application of Image Processing in Traffic Management and AnalysisIntroductionSmart Traffic Management SystemsReal-Time SystemData Analysis SystemReview WorkWorking of Real-Time Traffic ManagementReferences: Application of Image Processing and Data Science in Advancing Education InnovationIntroductionRole of Image Processing in EducationIntegrating Image Processing in Teaching and Learning in SchoolsRole of Image-Based Computerized Learning in EducationImportant Roles of Image Processing in EducationAssessing Creativity and Motivation in Image-Based Learning SystemsBuilding Character through Interactive MediaImage ProcessingImage AcquisitionImage EnhancementImage RestorationColor Image ProcessingWavelets and Multiresolution ProcessingImage CompressionMorphological ProcessingSegmentationRepresentation and DescriptionObject RecognitionLearning Content MappingLearners and Educators on the Image-Based Computerized EnvironmentTeaching PracticesRaising Learners AttainmentInequalities Reduction among LearnersDiscussionReferences: Application of Image Processing and Data Science in Advancing Agricultural DesignIntroductionImage Processing Techniques in AgricultureThermal ImagingComponents of Thermal ImagingFluorescence ImagingHyperspectral ImagingPhotometric (RGB) Feature-Based ImagingApplication of Digital Image Processing with Data Science in AgricultureManagement of CropIdentifying the Deficiencies of Nutrition in PlantsInspection of Quality of Fruits along with Their Sorting and GradingEstimation of Crop and Land and Tracking of ObjectIdentification of Diseases in PlantsPrecision FarmingWeed DetectionNewer Techniques in the Agriculture Support SystemAeroponic SystemArtificial Intelligence in AgricultureReferences

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