Image quality enhancement in 3D computational integral imaging by use of interpolation methods

Abstract

In this paper, we propose a computational integral imaging reconstruction (CIIR) method by use of image interpolation algorithms to improve the visual quality of 3D reconstructed images. We investigate the characteristics of the conventional CIIR method along the distance between lenslet and objects. What we observe is that the visual quality of reconstructed images is periodically degraded. The experimentally observed period is half size of the elemental image. To remedy this problem, we focus on the interpolation methods in computational integral imaging. Several interpolation methods are applied to the conventional CIIR method and their performances are analyzed. To objectively evaluate the proposed CIIR method, we introduce an experimental framework for the computational pickup process and the CIIR process using a Gaussian function. We also carry out experiments on real objects to subjectively evaluate the proposed method. Experimental results indicate that our method outperforms the conventional CIIR method. In addition, our method reduces the grid noise that the conventional CIIR method suffers from.

Resolution-enhanced Reconstruction of 3D Object Using Depth-reversed Elemental Images for Partially Occluded Object Recognitionz

“…Optical reconstruction tends to degrade the image quality due to the diffraction and limitation of optical devices. To overcome these problems, computational reconstruction was studied [6][7][8][9][10][11]. Computational reconstruction is a technique based on the ray-tracing analysis to simulate the ray propagation mechanism by using a computer.…”

“…The 3D image reconstructed with this technique does not have the problems caused by optical reconstruction as there are no optical devices involved. However, computational reconstruction also suffers from a few drawbacks such as low resolution, high computational cost, and interference between elemental images [9]. Many methods have been studied to overcome these problems [7][8][9][10][11].…”

“…However, computational reconstruction also suffers from a few drawbacks such as low resolution, high computational cost, and interference between elemental images [9]. Many methods have been studied to overcome these problems [7][8][9][10][11]. Recently, one of our authors proposed a reconstruction method using a digital depth-conversion method, which is called smart pixel mapping [12], for EIA to reduce the computational cost [13].…”

Computational Integral Imaging Reconstruction of 3D Object Using a Depth Conversion Technique

“…It can record and reconstruct 3D objects with full parallax, continuous viewing points and the use of white light [1][2][3][4][5][6]. However, there are several problems to be solved such as low resolution, narrow viewing angle, and pseudoscopic images.…”

“…In the VCR process, the EIA is digitally reconstructed by using a computer in order to obtain volumetric 3D images. CII has several problems to be solved such as a poor resolution of the reconstructed image [6,13], high computational cost [14], reconstruction limitation of far 3D objects [15], and so on.…”