Recognition and Perception of Images. Группа авторов
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3 Chapter 3Figure 3.1 Scheme of imaginative thinking.Figure 3.2 Types of imaginative thinking.Figure 3.3 The hierarchy of sensory images.Figure 3.4 Design image based on the symbols.Figure 3.5 Real images are converted to decorative symbols.Figure 3.6 The agglutination method in creation and imagination.Figure 3.7 The image elements of the makeup for Beijing Opera characters.Figure 3.8 The image in the project activities structure.Figure 3.9 An electric tower is a creative source for the image of brand-new cos...Figure 3.10 Stages of creating a project image.Figure 3.11 Stages of creating for costume design.Figure 3.12 The world-famous images of Charlie Chaplin, Marilyn Monroe and Salva...
4 Chapter 4Figure 4.1.1 Option 1. Welcome hugs.Figure 4.1.2 Option 2. Multi-level spiral.Figure 4.1.3 Option 3. Unification.Figure 4.1.4 Option 4. Continents.Figure 4.1.5 Option 5. Combinatorics.Figure 4.1.6 Option 6. Length.Figure 4.2.1 The Concept of “Rebirth”.Figure 4.2.2 The Concept of “Variability”.Figure 4.2.3 The Concept of “Riddle”.Figure 4.2.4 The concept of “Infinity of development”.
5 Chapter 5Figure 5.1 Illustration of representations in feature space learned by (a) exist...Figure 5.2 Illustration of the expected separations of the observation x, which ...Figure 5.3 Framework of our facial expression recognition model used for trainin...Figure 5.4 Failed case of (a) triplet loss, (b) (N+1)-tuplet loss, and (c) Coupl...Figure 5.5 Failed case of (a) triplet loss, (b) (N+1)-tuplet loss, and (c) Coupl...Figure 5.6 The training loss of different methods on SFEW validation set. The va...Figure 5.7 t-SNE visualization of images in Extended YaleB. The original images ...Figure 5.8 Using MI-FLF to swap some face attributes, while keeping their ID and...
6 Chapter 6Figure 6.1 Selection of necessary information on images.Figure 6.2 Creation of objects with information on images.Figure 6.3 Display of images in the form of tiles (ImageStrip).Figure 6.4 Display form of user interface.Figure 6.5 Database diagram.Figure 6.6 Main steps of text determination algorithm.Figure 6.7 Main steps of the Russian text recognition algorithm.Figure 6.8 Work of algorithm recognizing the English text.Figure 6.9 Cloud of Russian words specifying the objects of non-political class.Figure 6.10 Cloud of Russian words specifying the objects of political class.Figure 6.11 Cloud of English words specifying the objects of non-political class...Figure 6.12 Cloud of English words specifying the objects of political class.Figure 6.13 Frequency diagram for cities with the political activity.
7 Chapter 7Figure 7.1 Well-structured scene images, designed for the image understanding le...Figure 7.2 Simplest weakly-structured (camouflaged) scene images.Figure 7.3 Examples of raw scene images.Figure 7.4 The different kinds of low-resolution digital image displaying [Buten...Figure 7.5 The different types of interior/exterior topology objects: (a) – 8/8 ...Figure 7.6 Vague regions and their regularization example.Figure 7.7 The example of histogram analysis: original image (a) and the primary...Figure 7.8 The example of digital image encapsulation (gray-level image object d...Figure 7.9 3-D view of encapsulated image granules.Figure 7.10 Example of a spatial encapsulation by the +G2 Cartesian granule.Figure 7.11 Subsets of encapsulated Cartesian granules on the plane.Figure 7.12 The common positions of two granules diagram.Figure 7.13 (a) the result of the Algorithm 1 execution over the solid points cl...Figure 7.14 Three-level structure of GDMS on the basis of relational DBMS.Figure 7.15 Methodology of granulation of the image by L. Zadeh.Figure 7.16 Optimal structure of the granulated GDMS.Figure 7.17 The successive stages (1)-(6) of Automated target Detection for the ...Figure 7.18 The source character images for the classification.Figure 7.19 The examples of granulated character images.Figure 7.20 The fuzzy relation matrix graphic representations for the granulated...Figure 7.21 Corrupted character images examples.Figure 7.22 Different color space models in Cylindrical and Conical coordinates:...Figure 7.23 Google Earth image of seashore near Barcelona (a) and its RGB color ...Figure 7.24 Different projections of the granulated seashore image color histogr...
8 Chapter 8Figure 8.2.1 Geometry of 3-D ISAR scenario.Figure 8.2.2 Two 2-D coordinate systems built in the ISAR signal plane depicted ...Figure 8.2.3 The coordinate systems O’XY and
built in stationary 2-D ISAR imag...Figure 8.2.4 2-D ISAR geometry.Figure 8.3.1 Traveling of the object trough range bins in case rectilinear movem...Figure 8.3.2 2-D geometrical model of aircraft MiG-35 in 64x64 pixels grid.Figure 8.3.3 LFM ISAR signal: real part (a), and imaginary part (b).Figure 8.3.4 LFM ISAR signal after correlation range compression: real (a), and ...Figure 8.3.5 3-D isometric projection of the object image after FFT azimuth comp...Figure 8.3.6 LFM SAR signal: real part (a), and imaginary part (b).Figure 8.3.7 LFM ISAR signal after correlation range compression: real part (a),...Figure 8.3.8 Aircraft Mig-35 final image in 3-D isometric projection (a), and in...Figure 8.3.9 Unwrapped phase history Ф0(p) and extrapolated curve Ф(p) (a), (b –...Figure 8.3.10 Phase difference ΔФ(p).Figure 8.3.11 First cost function C1 = M(A) (a), and second cost function C2(A) ...Figure 8.3.12 Aircraft Mig-35 – final image, obtained after autofocusing procedu...Figure 8.3.13 ISAR signal with Barker’s phase code modulation in 3-D isometric p...Figure 8.3.14 Barker’s PCM ISAR signal (isometric projection) after correlation ...Figure 8.3.15 ISAR image (isometric projection) after FFT azimuth compression (a...Figure 8.3.16 Family of phase correction functions (a) Ф(p), and three cases of ...Figure 8.3.17 3-D view of the surface, described by the image cost function C1(p...Figure 8.3.18 Aircraft F-18 image: p0 = 250, p = 0.01 (a), p = 0.02 (b).Figure 8.3.19 Aircraft F-18 image: p0 = 250, p = 0.05- unfocused (a), p = 0.06-f...Figure 8.4.1 3-D geometry of the aircraft F18..Figure 8.4.2 Real and imaginary parts of the ISAR signal.Figure 8.4.3 Real and imaginary parts of the ISAR signal after demodulation.Figure 8.4.4 Isometric 3-D ISAR image.Figure 8.4.5 Final image (a) and power normalized image (b).Figure 8.4.6 Autofocusing by p = q = 58 and r = 30.Figure 8.4.7 Autofocusing by p = q = 58 and r = 46.Figure 8.4.8 Autofocusing by p =q = 58 and r = 60.Figure 8.4.9 A surface of the entropy function using as a cost function in the a...Figure 8.4.10 ISAR signal formation with complementary phase code modulation (fi...Figure 8.4.11 Real (a) and imaginary (b) component of the ISAR signal modulated ...Figure 8.4.12 Real (a) and imaginary (b) component of the ISAR signal, modulated...Figure 8.4.13 Real (a) and imaginary (b) part of the ISAR signal, modulated by f...Figure 8.4.14 Real (a) and imaginary (b) part of the ISAR signal, modulated by s...Figure 8.4.15 The image of the aircraft MiG-35, obtained from ISAR signal, modul...Figure 8.4.16 Aircraft MiG-35 image (256 levels of grey color scale) from CPCM I...Figure 8.4.17 Discrete structure of the object depicted in the space of the regu...Figure 8.4.18 Reconstructed ISAR image: by step p = 1 (a), by step p = 2 (b), by... 9 Chapter 9Figure 9.1 Multidimensional ESF of multispectral image.Figure 9.2 Probability spread function of multispectral image.Figure 9.3 Probability density distribution of a multispectral image.Figure 9.4 The equivalent spatial resolution determining by equivalent PSF of th...Figure 9.5 Determining the spectral reflectance value of x band using the identi...Figure 9.6 Multispectral imagery resolution enhancement dataflow diagram.Figure 9.7 ASTER multispectral satellite image (Odessa, Ukraine, 24.09.2007, 9 s...Figure 9.8 The results of the satellite imagery band downsampling by a factor of...Figure 9.9 Schematic representation of the analyzed subpixels on pixel grids of ...Figure 9.10 Basic types of subpixels relative location.Figure 9.11 The series-parallel system examples.Figure 9.12 Selection of subpixel reallocating rule.Figure 9.13 Sentinel 2 MSI fragment with false color combination of band 5 (705 ...Figure 9.14 Thermal infrared atmospheric windows (3-5 μm – mid-wave infrared ran...Figure 9.15 Raw satellite images of central part of Kyiv city (Ukraine): 10 m Se...Figure 9.16 NDVI-emissivity relationship approximation [Zaitseva et al., 2019].Figure 9.17 Visual comparison between the resolution of raw longwave-infrared da...Figure 9.18 Spatial resolution enhancement flowchart.Figure 9.19 LST image in the spatial domain (a) and its Fourier amplitude spectr...Figure 9.20 Extraction of low- and high-frequency components of LST data.Figure 9.21 General flowchart of frequency component merging for LST spatial res...Figure 9.22 The visual difference between low-resolution