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The fundamental domain F , fundamental weights (ω1, ω2), and simple roots (α1, α2).

The fundamental domain F , fundamental weights (ω1, ω2), and simple roots (α1, α2).

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The current camera has made a huge progress in the sensor resolution and the lowluminance performance. However, we are still far from having an optimal camera as powerful as our eye is. The study of the evolution process of our visual system indicates attention to two major issues: the form and the density of the sensor. High contrast and optimal s...

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... discrete transform of Lie group provides a possibil- ity for frequency analysis of discrete functions defined on a triangle or hexagonal grids [26]. Figure 5 shows an example of fundamental domain F , the fundamen- tal weights (ω 1 , ω 2 ) of the orbit function in the form of a hexagon. The similarity of the grid in the funda- mental domain of a certain orbit function from Weyl group to the grid of hexagonal images makes the orbit functions interesting for the hexagonal computation in which it becomes possible to process hexagonal images without any further transformation. ...

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... Some of the obstacles in developing new sensor arrangements are the difficulty in manufacturing, the cost, and rigidity of hardware components. The virtual deformation of the sensor arrangement [3] provides new possibilities for overcoming such obstacles. We need strong arguments to convince the involved partners in sensor development to implement the virtual deformation ideas. ...
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... Figure 14 shows the mean (a) and variance (b) of ratio values of ten corresponding pixel sets between each SQ and to Hex_E image. The mean (a) shows the nonlinear relation between SQ to Hex_E which was previously shown in [3,18]. The mean (a) also shows that the relation between to Hex_E is similar to the relation between SQ to Hex_E and behaves in a nonlinear manner. ...
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... The results show the dynamic range is widened and tonal level is extended. (b) The grid and pixel are hexagonal and square respectively and there is no or fixed gap in [29], where the hexagonal grid is generated by a half-pixel shifting, its results show that the generated hexagonal images are superior in detection of curvature edges to the square images. (c) The grid and pixel are hexagonal and there is no gap [30]. ...
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... In the regular hexagonal lattice, the vertical and horizontal pitch ratio is ≈ 3 : 2 0.8660, and in the "brick wall" approach, the ratio is 1:1, while in the "hyperpel" approach, the ratio is 7:8 = 0.8750. Therefore, the "hyperpel" approach can be treated as a good approximation and it is the most common displaying approach used in current hexagonal image research [2,3,[16][17][18]. ...
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Chapter
The quality assessment of a high dynamic image is a challenging task. The few available no reference image quality methods for high dynamic range images are generally in evaluation stage. The most available image quality assessment methods are designed to assess low dynamic range images. In the paper, we show the assessment of high dynamic range images which are generated by utilizing a virtually flexible fill factor on the sensor images. We present a new method in the assessment process and evaluate the amount of improvement of the generated high dynamic images in comparison to original ones. The results show that the generated images not only have more number of tonal levels in comparison to original ones but also the dynamic range of images have significantly increased due to the measurable improvement values.