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Download Theoretical foundations of digital imaging using MATLAB PDF free

By Applied Electronics - Monday, February 27, 2017 No Comments
Download Theoretical foundations of digital imaging using MATLAB PDF free.

Content: Introduction Imaging Goes Digital Mathematical Preliminaries Mathematical Models in Imaging Signal Transformations Imaging Systems and Integral Transforms Statistical Models of Signals and Transformations Image Digitization Principles of Signal Digitization Signal Discretization Image Sampling Alternative Methods of Discretization in Imaging Devices Single Scalar Quantization Basics of Image Data Compression Basics of Statistical Coding Discrete Signal Transformations Basic Principles of Discrete Representation of Signal Transformations Discrete Representation of the Convolution Integral Discrete Representation of Fourier Integral Transform Discrete Representation of Fresnel Integral Transform Discrete Representation of Kirchhoff Integral Hadamard, Walsh, and Wavelet Transforms Discrete Sliding Window Transforms and "Time-Frequency" Signal Representation Digital Image Formation and Computational Imaging Image Recovery from Sparse or Nonuniformly Sampled Data Digital Image Formation by Means of Numerical Reconstruction of Holograms Computer-Generated Display Holography Computational Imaging Using Optics-Less Lambertian Sensors Image Resampling and Building Continuous Image Models Perfect Resampling Filter Fast Algorithms for Discrete Sinc Interpolation and Their Applications Discrete Sinc Interpolation versus Other Interpolation Methods: Performance Comparison Numerical Differentiation and Integration Local ("Elastic") Image Resampling: Sliding Window Discrete Sinc Interpolation Algorithms Image Data Resampling for Image Reconstruction from Projections Image Parameter Estimation: Case Study-Localization of Objects in Images Localization of Target Objects in the Presence of Additive Gaussian Noise Target Localization in Cluttered Images Image Perfecting Image Perfecting as a Processing Task Possible Approaches to Restoration of Images Distorted by Blur and Contaminated by Noise MMSE-Optimal Linear Filters for Image Restoration Sliding Window Transform Domain Adaptive Image Restoration Multicomponent Image Restoration and Data Fusion Filtering Impulse Noise Correcting Image Grayscale Nonlinear Distortions Nonlinear Filters for Image Perfecting Index Exercises and References appear at the end of each chapter.

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