We present experimental results of imaging and digital super-resolution in a multiaperture miniature folded imaging architecture called PANOPTES. We prove the feasibility of integrating folded imagers within a steerable multi-aperture framework while maintaining thin profiles. ©2009 Optical Society of America OCIS codes: (110.0110) Imaging systems; (100.6640) Superresolution

Kurzfassung. Unter dem Begriff der Superresolution versteht man Algorithmen aus der Bildverarbeitung zur Auflösungssteigerung mittels niedrig aufgelöster Bilddaten. Die Roboterisierung eines mobilen C-Bogens bietet nun die Möglichkeit die physikalische Auflösung des Aufnahmesystems mittels dieser Techniken zu erhöhen. Anhand eines synthetischen CT-Phantoms wurden hierbei gängige Super-Resolutio...

Hyper-Resolution, a new technique for super-resolution reconstruction of images, is based on matching lowresolution target image details to their high-resolution counterparts from an image database. Central to the algorithm is a novel transform of image content from the orthogonal pixel space to a parametric space structured around edges. This approach offers improved quality, more flexibility ...

High Resolution images can be reconstructed from several blurred, noisy and aliased low resolution images using a computational process know as super resolution reconstruction. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. In this paper we concentrate on a special case of super resolution problem where the wrap i...

This paper proposes high resolution RGB image supported near infrared (NIR) image super resolution method. In general, NIR image has low resolution characteristics. To show small image on bigger screen, super resolution method is applied to generate bigger image to fit the display. As CCD camera take colors images with high resolution, therefore one many extract helpful features for NIR image s...

Face Hallucination is a super-resolution technique to obtain high-resolution facial images by taking low-resolution facial images as input. In this paper problem of face hallucination has been approached by using sparse Representation. The image has to be subdivided into different segments so that image pixel information can be retrieved easily from each segment. Each small patch of the image h...

Reconstruction-based super-resolution frommotion video has been an active area of study in computer vision and video analysis. Image alignment is a key component of super-resolution algorithms. Almost all previous super-resolution algorithms have assumed that standard methods of image alignment can provide accurate enough alignment for creating super-resolution images. However, a systematic stu...

We consider the problem of scaling deep generative shape models to high-resolution. To this end, we introduce a novel method for the fast up-sampling of 3D objects in voxel space by super-resolution on the six orthographic depth projections. We demonstrate the training of object-specific super-resolution CNNs for depth maps and silhouettes. This allows us to efficiently generate high-resolution...

Optical imaging and lithography, the processes in which spatial patterns are resolved or transferred onto a detector or substrate via photons, cannot produce spatial features that are much smaller than the wavelength of light. This limitation has its roots in classical diffraction [1], which had been considered as a fundamental limit to all such imaging systems. Most notably, computer chip manu...