Correcting distortion and braiding of micro-images from multi-aperture imaging systems

Abstract

Multi-aperture imaging systems inspired by insect compound eyes promise advances in both miniaturization and cost reduction of digital camera systems. Instead of a single lens stack with size and sag in the order of a few millimeters, the optical system consists of an array of microlenses. At a given field of view of the complete system, the focal lengths of the microlenses is a fraction of the focal length of a single-aperture system, reducing track length and increasing depth of field significantly. As each microimage spans only a small field of view, the optical systems can be simple. Because the microlenses have a diameter of hundreds of microns and a sag of tens of microns, they can be manufactured cost-effectively on wafer scale and with high precision. However, reaching a sufficient resolution for applications such as camera phones has been a challenge so far. We demonstrate a multi-aperture color camera system with approximately VGA resolution (700x550 pixels) and a remarkably short track length of 1.4 mm. The algorithm for correcting optical distortion of the microlenses and combining the microimages into a single image is the focus of this presentation

Artificial compound eye: a survey of the state-of-the-art

“…In Nitta et al (2006), to further improvement of the method, Nitta et al introduced an iterative back projection method (IBP), where the pixel rearrange method was first applied to obtain the initial image and the back projection method was iteratively applied to refine the image. Except for the pixel rearrange method, lots of image reconstruct methods were also discussed in planar artificial compound eye (Kanaev et al 2007;Boussaid 2008, 2009;Horisaki et al 2009;Oberdörster et al 2011;Mendelowitz et al 2013;Wood et al 2004Wood et al , 2005Wood et al , 2006Li et al 2007Chan et al 2006b;Choi and Schulz 2008;Tudela et al 2008b, a). Kanaev et al (2007) presented a scene-independent method, in which the final image with high resolution could be reconstructed only based on the accurate relative pixel shifts.…”

“…The lowfrequency component was utilized to generate the final smooth image and the high-frequency component was used in the depth estimation. Based on eCley system, a braiding algorithm to restore the final image was discussed in Oberdörster et al (2011). Various image reconstruct methods for planar artificial compound eye are summarized in Table 6, where the advantages and limitations of different methods are compared.…”

Dense lightfield reconstruction from multi aperture cameras

“…An example image is presented in Figure 4 (left). Details about the underlying pre-processing can be found in [14]. These single channel images are used as input to our processing chain.…”

Geometry based three-dimensional image processing method for electronic cluster eye

“…In [14], a sum of squared difference (SSD) evaluation based backproject method was described based on the fact that a back-project method will result in poor reconstruction performance when the object is located at the wrong position. Especially for eCley, a braiding algorithm was introduced in [30,31] to obtain the reconstructed image with the final resolution 640*480. The final image can only focus on a specified distance at a time.…”

“…Further, a sharply focused image and a depth map can be gained. Compared with the methods in [30,31,59], G3D has three main advantages:…”