Digital image processing and analysis is a field that continues to experience rapid growth, with a diversity of applications ranging from areas such as space exploration to the entertainment industry. This title covers different areas of digital image processing and analysis, both human and computer vision applications.

Section I Introduction to Digital Image Processing and AnalysisDigital Image Processing and AnalysisOverviewImage Analysis and Computer VisionImage Processing and Human VisionKey PointsExercisesReferencesFurther ReadingComputer Imaging SystemsImaging Systems OverviewImage Formation and SensingCVIPtools SoftwareImage RepresentationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection II Digital Image Analysis and Computer VisionIntroduction to Digital Image AnalysisIntroductionPreprocessingBinary Image AnalysisKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSegmentation and Edge/Line DetectionIntroduction and OverviewEdge/Line DetectionSegmentationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingDiscrete TransformsIntroduction and OverviewFourier TransformDiscrete Cosine TransformDiscrete Walsh-Hadamard TransformDiscrete Haar TransformPrincipal Components TransformFilteringDiscrete Wavelet TransformKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingFeature Analysis and Pattern ClassificationIntroduction and OverviewFeature ExtractionFeature AnalysisPattern ClassificationKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection III Digital Image Processing and Human VisionDigital Image Processing and Visual PerceptionIntroduction and OverviewHuman Visual PerceptionImage Fidelity CriteriaKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingImage EnhancementIntroduction and OverviewGray-Scale ModificationImage Sharpening Image SmoothingKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingImage Restoration and ReconstructionIntroduction and OverviewNoise ModelsNoise Removal Using Spatial FiltersDegradation FunctionFrequency Domain FiltersGeometric TransformsImage ReconstructionKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingImage CompressionIntroduction and OverviewLossless Compression MethodsLossy Compression MethodsKey PointsExercisesSupplementary ExercisesReferencesFurther ReadingSection IV Programming and Application Development with CVIPtoolsCVIPlabIntroduction to CVIPlabToolkits, Toolboxes, and Application LibrariesCompiling and Linking CVIPlabImage Data and File StructuresCVIP ProjectsApplication DevelopmentIntroduction and OverviewCVIP Algorithm Test and Analysis ToolCVIP Feature Extraction and Pattern Classification ToolSkin Lesion Classification Using Relative Color FeaturesAutomatic Segmentation of Blood Vessels in Retinal ImagesClassification of Land Types from Satellite Images Using Quadratic Discriminant Analysis and Multilayer PerceptronsWatershed-Based Approach to Skin Lesion Border SegmentationFaint Line Defect Detection in Microdisplay (CCD) ElementsMelanoma and Seborrheic Keratosis Differentiation Using Texture FeaturesCompression of Color Skin Tumor Images with Vector Quantization ReferencesCVIPtools C (R) Function LibrariesIntroduction and OverviewArithmetic and Logic Library: ArithLogic.libBand Image Library: Band.lib Color Image Library: Color.libCompression Library: Compression.libConversion Library: Conversion.libDisplay Library: Display.libFeature Extraction Library: Feature.libGeometry Library: Geometry.libHistogram Library: Histogram.libImage Library: Image.libData Mapping Library: Mapping.libMorphological Library: Morphological.libNoise Library: Noise.libSegmentation Library: Segmentation.libSpatial Filter Library: SpatialFilter.lib Transform Library: Transform.libTransform Filter Library: TransformFilter.libSection V AppendicesCVIPtools CDInstalling and Updating CVIPtools CVIPtools Software OrganizationCVIPtools C (R) FunctionsCommon Object Module (COM) Functions: cviptools.dllCVIP ResourcesIndex

"Where needed, chapters are extremely well illustrated with full color images supplied where appropriate. ... My impression of this textbook is that it can be easily used as a basis for instruction in a variety of image processing and analysis areas in undergraduate and graduate work in fields from computer science to electrical to biomedical engineering and in a number of related fields of endeavor involved in image perception and analysis. ... The text is written at a junior-year or above level and used as a basis for advanced studies involving images. It is quite up to date. I recommend it highly."-Paul H. King, Vanderbilt University, IEEE Pulse, July/August 2012 "This is a nicely presented book and the topics it covers in depth are well described. ... if you are looking for a book on the basics of image processing complete with some ready-made software to let you work through the ideas, this is a good choice. Needless to say it would make a good course text ..."-Mike James, IProgrammer, September 2011 "The text, which is richly illustrated with both drawings and example images, and the CVIPtools package are highly integrated. This creates a learning environment that is particularly suited to students, computer scientists, and application developers. ... Altogether, the author has produced a book that presents both the practical and theoretical aspects of digital image processing in a way that is efficient for learning, as well as research- and application-oriented development. He does an excellent job of showing how algorithms work and what the results look like. ... The CVIPtools application and libraries are very useful. Compared with the first edition, two newly added software tools, the Computer Vision and Image Processing Algorithm Test and Analysis Tool (CVIP-ATAT) and the CVIP Feature Extraction and Pattern Classification Tool (CVIP-FEPC) offer a more complete set of tools for developing and testing algorithms. ... Overall, this is an excellent text for the student or professional looking for a practical introduction to or an overview of the wide world of digital image processing and analysis."-Jeffrey Snyder and Elena Fedorovskaya, Kodak Research Laboratories, Rochester, New York, Journal of Electronic Imaging, Jul-Sep 2011/Vol. 20(3)