The 14 reference contexts in paper M Sutkowski, Ya. Saukova N., М. Сутковский, Е. Савкова Н. (2017) “ИССЛЕДОВАНИЕ ДИНАМИЧЕСКОГО ДИАПАЗОНА ЦИФРОВОЙ КАМЕРЫ НА ОСНОВЕ ТЕХНОЛОГИЙ ОБРАБОТКИ ЦИФРОВЫХ ИЗОБРАЖЕНИЙ // RESEARCH OF DIGITAL CAMERA DYNAMIC RANGE ON THE IMAGING PROCESSING BASIS” / spz:neicon:pimi:y:2017:i:3:p:271-278

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    Standard methods for solving this problem are based on the dynamic range compression of the plots. Currently compression procedures are used to reproduce image details that are situated in the region closed to the saturation matrix photodetector
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    . So it is necessary to move the point A into the region of the inflection of light characteristics of the signal, which produces a brighter light for compressing the amplitude (interval E1–E2, Figure 1a).
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    However, when it is necessary to determine illuminance (brightness) in different points of the object simultaneously a principally new approach is needed. Aspects of cameras range compression are discussed in
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    and [3]. Contrast extension leads to a «splitting» of quantization levels that appear in the histogram as a comb. The combined method of dynamic range controlling by software tools in [4] is described.
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    However, when it is necessary to determine illuminance (brightness) in different points of the object simultaneously a principally new approach is needed. Aspects of cameras range compression are discussed in [2] and
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    . Contrast extension leads to a «splitting» of quantization levels that appear in the histogram as a comb. The combined method of dynamic range controlling by software tools in [4] is described.
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    Aspects of cameras range compression are discussed in [2] and [3]. Contrast extension leads to a «splitting» of quantization levels that appear in the histogram as a comb. The combined method of dynamic range controlling by software tools in
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    is described. The method is based on the dynamic range stretching in dark areas and compression in the blown highlights area of image. However these technologies are used only for visual improvement of images quality and don’t allow determining the intensity significantly.
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    However these technologies are used only for visual improvement of images quality and don’t allow determining the intensity significantly. They consider the patterns and effects of visual perceptions such as light and color adaptation, the contrast and the contours of fine details etc.
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    . a b c Figure 1 – Electronic methods of dynamic range compression: a – linear compression with the displacement of the point of saturation down; b – nonlinear compression after the inflection point for different contrast; c – options linear compression with the same contrast This method is based on repeated digital regarding of extended objects and digital images
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    The problem of determining the illumination at the object is solved by expanding the dynamic range of optical measurement software. The method developed in the Scientific Research Laboratory of optics and electronics instrument making (Belarusian National Technical University, Minsk, Belarus)
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    and tested in the Laboratory of Photonics of the Institute of Optoelectronics and Microelectronics (Warsaw University of Technology, Warsaw, Poland) allows doing photometric measurements in real time with the specified characteristics error.
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    The main idea of this method is to do series of digital images of the same object and reference samples with different exposures and process the images in RGB and RAW formats. Format RGB provides the ability to define intensity in red, green, and blue color channels of images
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    . There are different technologies of objects multiple registrations with increasing the time of exposure for creating of HRDI images [9, 10]. But they apply in computer games and design. And the technology which is described provides an opportunity to obtain quantitative data of photometric and colorimetric parameters of the object.
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    Format RGB provides the ability to define intensity in red, green, and blue color channels of images [8]. There are different technologies of objects multiple registrations with increasing the time of exposure for creating of HRDI images
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    [9, 10]
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    . But they apply in computer games and design. And the technology which is described provides an opportunity to obtain quantitative data of photometric and colorimetric parameters of the object. The experimental research of a digital camera dynamic range To ensure metrological traceability the sets of achromatic and chromatic samples were done on the colorimetric and calibrated
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    The metrological traceability of measurement results is provided by reference to the initial samples (called by authors as a line sources with equal brightness) which are nonpoint sources of light acting as the measures in measurements
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    . Within each of the line light sources should vary in brightness with a step depending on the specific measuring task. Thus we can construct a set of calibration dependencies for each source showing the dependence of numerical representation of intensity values (y-axis) of the color channels from the exposure H (x-axis) – R(t), G(t), B(t), an example of which is given
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    Thus we can construct a set of calibration dependencies for each source showing the dependence of numerical representation of intensity values (y-axis) of the color channels from the exposure H (x-axis) – R(t), G(t), B(t), an example of which is given in Figure 5
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    . Further according to mated for each consecutive pairs of sources for example one line for the one time. The values of intensities of R, G, B for exposure H pending solid lines in the figure on the y-axis.
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    of linearity of the calibration characteristics of the measurement method we can determine on the y-axis conditional point R'n outside physical dynamic range and carry out the normalization of the intensities of R, G, B, adapting them to new values, introducing appropriate broadening coefficients directly in a standardized model transformation color spaces RGB→XYZ
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    : (2) (3) (4) where X, Y, Z – coordinates of the color space XYZ; anm – the standardized weighting of intensities R, G, B, kR, kG, kB – expanding the coefficients calculated by the formulas [4]: (5) The highest value of the digital intensity image is given in the denominators.
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    of the intensities of R, G, B, adapting them to new values, introducing appropriate broadening coefficients directly in a standardized model transformation color spaces RGB→XYZ [4]: (2) (3) (4) where X, Y, Z – coordinates of the color space XYZ; anm – the standardized weighting of intensities R, G, B, kR, kG, kB – expanding the coefficients calculated by the formulas
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    : (5) The highest value of the digital intensity image is given in the denominators. It is dependant on the actual digital quantization level, the highest number is repesented by the 2n where n is the number of bits used.
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    The nominal level of quantization represent the ellipsoids of different volumes in three-dimensional color spaces, and the minimum (definitely) uncertainty ellipses is determined by the Mac-Adam
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    . However the constant value of the nominal level of quantization can be maintained in the RGB color space by the mathematical methods of the increment intensity. There is a possibility to define the color characteristics of self-luminous objects and to enter correction factors for secondary emitters by applying models of chromatic adaptation Von-Crease, CIECAM02, Fairchild and others
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    There is a possibility to define the color characteristics of self-luminous objects and to enter correction factors for secondary emitters by applying models of chromatic adaptation Von-Crease, CIECAM02, Fairchild and others
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    . Data conversion must be performed for each color channel. It should be consider surface properties (reflectance) and parameters of shooting in the calculations. The Figure 6 explains the essence of the developed model.
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