An Introduction to Digital Image Processing

accuracy adjustment applied array assigned bands Bayesian bilinear interpolation blue brightness cc(kmax chromaticity classification cluster coefficients color space control points coordinates correlation cubic convolution defined derived digital image processing dimensional histogram distribution edge chains equation error Euclidean distance example Fourier transform frequency function Gaussian geometric given giving gradient green grid point histogram equalization image histogram input image input pixel inverse iterated J-M distance kmax Laplacian linear Luminosity Function mask matrix maximum likelihood measure method noise normally number of pixels operations output image parameters pixel value mapping pixel with value PL/I point spread function polynomials principal components priori probabilities problem region registered resampling RGB display sample sampled signal search area segmentation shown in Figure signal smoothing filters spatial specified standard deviation t₁ threshold tion training data tristimulus typically vector Vout wavelength