Abstract

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 sampling properties of our visual spatial arrangement are related directly to the densely hexagonal form. In this paper, we propose a novel software-based method to create images on a compact dense hexagonal grid, derived from a simulated square sensor array by a virtual increase of the fill factor and a half a pixel shifting. After that, the orbit functions are proposed for a hexagonal image processing. The results show it is possible to achieve an image processing in the orbit domain and the generated hexagonal images are superior, in detection of curvature edges, to the square images. We believe that the orbit domain image processing has a great potential to be the standard processing for hexagonal images.

Highlights

  • Nowadays, the ubiquitous influence of cameras in our life is undoubtable and this is thanks to the current camera sensory technique, which has made a huge progress on increasing the sensor resolution and the low-luminance performance [1]

  • The corresponding logarithm of histograms of the hexagonal and square-pixel images in Figure 7 is shown in Figure 8, which indicates that in both recovered square-pixel images and generated hexagonal images the tonal levels are extended, and the tonal ranges are wider in comparison to the simulated camera sensor image

  • This is reasonable as far as the hexagonal images are obtained by half-pixel shifting of the square-pixel image recovered with the enhanced fill factor

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Summary

Introduction

The ubiquitous influence of cameras in our life is undoubtable and this is thanks to the current camera sensory technique, which has made a huge progress on increasing the sensor resolution and the low-luminance performance [1]. As the sensor pixel size becomes smaller, a smaller die size detection, gaining higher spatial resolution and obtaining lower signal-to-noise ratio are required; all in cost of a lower dynamic range and a fewer number of tonal levels. Rods, another type of photoreceptors with non-color property, first appear at about 100 μm from the foveal center and are smaller than the cones

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