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A Concise Introduction To Image Processing Using C++ 2008 Edition at Meripustak

A Concise Introduction To Image Processing Using C++ 2008 Edition by Meiqing Wang, Choi-Hong Lai , Taylor & Francis Ltd

Books from same Author: Meiqing Wang, Choi-Hong Lai

Books from same Publisher: Taylor & Francis Ltd

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  • General Information  
    Author(s)Meiqing Wang, Choi-Hong Lai
    PublisherTaylor & Francis Ltd
    ISBN9781584888970
    Pages268
    BindingHardback
    LanguageEnglish
    Publish YearNovember 2008

    Description

    Taylor & Francis Ltd A Concise Introduction To Image Processing Using C++ 2008 Edition by Meiqing Wang, Choi-Hong Lai

    Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems. The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying CD-ROM contains code for all algorithms.Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool. Basic Concepts of ImagesAnalogue SignalsDigital SignalsGrey-Scale ImagesColour ImagesImage Storage FormatsVideoExercisesReferencesPartial Code ExamplesBasic Image Processing ToolsCorrelation Operation and Convolution OperationFourier TransformThe Discrete Cosine TransformThe Gabor TransformThe Wavelet TransformFurther Reading: Orthogonality and CompletenessExercisesReferencesPartial Code ExamplesPreprocessing Techniques for ImagesPixel Brightness (Grey-Level) TransformationsConcepts and Models of Image PreprocessingImage SmoothingImage EnhancementImage RestorationProcessing Methods Using Partial Differential EquationsFurther ReadingExercisesReferencesPartial Code ExamplesImage SegmentationThresholdingEdge-Based SegmentationRegion-Based SegmentationFurther ReadingExercisesReferencesPartial Code ExamplesMathematical MorphologySome Basic Concepts of Set TheoryMorphology for Binary ImagesMorphology for Grey-Scale ImagesFurther ReadingExercisesReferencesPartial Code ExamplesImage CompressionImage Fidelity MetricsLossless CompressionLossy CompressionImage Compression Standards: JPEG and MPEGFurther ReadingExercisesReferencesPartial Code ExamplesIndex



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