The interpretation of the ''inverted'' retina of primates as an ''optoretina'' (a light cones transforming diffractive cellular 3D-phase grating) integrates the functional, structural, ...
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ISBN:
(纸本)0819426407
The interpretation of the ''inverted'' retina of primates as an ''optoretina'' (a light cones transforming diffractive cellular 3D-phase grating) integrates the functional, structural, and oscillatory aspects of a cortical layer. It is therefore relevant to consider prenatal developments as a basis of the macro-and micro-geometry of the inner eye. This geometry becomes relevant for the postnatal trichromatic: synchrony organization (TSO) as well as the adaptive levels of human vision (28 - 33). It will be shown that the functional performances, the trichromatisme in photopic vision, the monocular spatiotemporal 3D- and 4D-motion detection, as well as the Fourier optical image transformation. with extraction of invariances all became possible, To transform light cones into reciprocal gratings especially the spectral phase conditions in the eikonal of the geometrical optical imaging before the retinal 3D-grating become relevant first, then in the von Laue resp. reciprocal van Lane equation for 3D-grating optics inside the grating and finally in the periodicity of Talbot-/Fresnel-planes in the near-field behind the grating. It is becoming possible to technically realize - at least in same specific aspects - such a cortical optoretina sensor element with its typical hexagonal-concentric structure which leads to these visual functions.
In this paper, a novel image analysis technique is proposed, which may be performed prior to coding in order to decide what is the most significant information to encode. In the proposed system, the image to be coded ...
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ISBN:
(纸本)0819413208
In this paper, a novel image analysis technique is proposed, which may be performed prior to coding in order to decide what is the most significant information to encode. In the proposed system, the image to be coded is first partitioned into a large number of sub-blocks of N*N pixels. The blocks can then be stored into two major classes according to the level of the visual activity present. The classification is based on analyzing the local histogram within each sub-block. In this paper, we initially analyze the image blocks to separate uniform blocks from those that can be classified as non-uniform blocks. Adjacent uniform blocks with the same statistics are merged to form large blocks. These blocks can then be coded by their mean values. It is also shown that the non-uniform blocks may also be classified into three categories with different levels of activity.
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