Computer Image Processing and RecognitionImage formation and perception. Representation. Ebhancement and restoration. Reconstruction from projections. Digital television, encoding, and data compression. Scene understanding. Scene matcching and recognition. |
Contents
Introduction | 1 |
Scene Matching and Recognition | 4 |
Image Formation and Perception | 8 |
Copyright | |
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algorithm average Bandwidth Bandwidth Compression binary bit/pixel circulant matrix coding color components Compression computed computed tomography considered contrast convolution coordinates correlation corresponding covariance matrix curve defined density described determine Digital Image discrete discrete Fourier transform distance distribution edge encoding entropy equal equation estimate example Figure finite Fourier transform given gray level histogram Huang IEEE IEEE Trans image plane Image Processing Image Restoration input integral invariant inverse linear low-pass filter luminance mapping mean squared error measure method modulation noise nonlinear object obtained optical original image parameters Pattern Recognition picture elements pixels probability problem Proc produced projection quantization radar random rate distortion theory receptors reconstruction region response rotation sampling scene matching sequence shown in Fig signal solution spatial frequency spectral techniques theorem three-dimensional threshold tion transfer function transmission two-dimensional values vector visual system York zero Σ Σ