Three-dimensional resolvability in an integral imaging system

Abstract

The concept of three-dimensional (3D) resolvability of an integral imaging system is thoroughly investigated in this research. The general concept of 3D resolution fails to describe the 3D discrimination completely. Then the concepts of the depth-resolution plane and lateral-resolution plane are introduced to show the difference between the conventional 3D spatial resolution and the newly introduced 3D resolvability. Therefore, the different properties of these planes for differentiating lateral spatial variations and axial variations are analyzed in this paper. The theoretical statements are demonstrated experimentally.

Improved multi-camera smart traffic surveillance system for resilient cities

“…On the other side, optical three-dimensional (3D) imaging techniques are able to extract the 3D image information and thus 3D objects location through the principles of geometrical and di ractive optics from the same set of multi-camera images [16][17][18]. The main advantage of using optical 3D imaging concepts in addition to image processing techniques is to make use of optical concepts when image processing fails to give accurate response.…”

Resolution Analysis of Axially Distributed Image Sensing Systems under Equally Constrained Resources

“…The ADS scheme can provide simple recording architecture by translating a single camera along its optical axis. The recorded high-resolution elemental images generate the clear 3D slice images for the partially occluded 3D objects compared with the conventional integral imaging method [6][7][8][9][10][11][12][13][14][15][16]. The capacity of this method to collect 3D information is related to the object location from the optical axis.…”

Improved resolution three-dimensional integral imaging using optimized irregular lens-array structure

“…Such a study necessitates a quantitative gauge to measure the level of achievable lateral and depth resolution in InI systems. This has not been possible until very recently, when object-independent models based on the concept of sampling rays were introduced to quantify the lateral and depth resolution [13]. A sampling ray connects the center of each pixel on the display device to the center of the corresponding lens in the lens array and thus carries the information necessary for image reconstruction [13][14][15].…”

“…This has not been possible until very recently, when object-independent models based on the concept of sampling rays were introduced to quantify the lateral and depth resolution [13]. A sampling ray connects the center of each pixel on the display device to the center of the corresponding lens in the lens array and thus carries the information necessary for image reconstruction [13][14][15]. The intersection point of each sampling ray and the image plane is referred to as the sampling point [13].…”

“…A sampling ray connects the center of each pixel on the display device to the center of the corresponding lens in the lens array and thus carries the information necessary for image reconstruction [13][14][15]. The intersection point of each sampling ray and the image plane is referred to as the sampling point [13]. Given that two or even more sampling rays can intersect with each other at a specific image plane, the concept of the order of the sampling points was introduced to enumerate the intersecting sampling rays.…”