Portable and cost-effective pixel super-resolution on-chip microscope for telemedicine applications.
ABSTRACT We report a field-portable lensless on-chip microscope with a lateral resolution of <1 μm and a large field-of-view of ~24 mm(2). This microscope is based on digital in-line holography and a pixel super-resolution algorithm to process multiple lensfree holograms and obtain a single high-resolution hologram. In its compact and cost-effective design, we utilize 23 light emitting diodes butt-coupled to 23 multi-mode optical fibers, and a simple optical filter, with no moving parts. Weighing only ~95 grams, we demonstrate the performance of this field-portable microscope by imaging various objects including human malaria parasites in thin blood smears.
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ABSTRACT: A new approach toward increasing spatial resolution is required to overcome the limitations of the sensors and optics manufacturing technology. One promising approach is to use signal processing techniques to obtain an high-resolution (HR) image (or sequence) from observed multiple low-resolution (LR) images. Such a resolution enhancement approach has been one of the most active research areas, and it is called super resolution (SR) (or HR) image reconstruction or simply resolution enhancement. In this article, we use the term "SR image reconstruction" to refer to a signal processing approach toward resolution enhancement because the term "super" in "super resolution" represents very well the characteristics of the technique overcoming the inherent resolution limitation of LR imaging systems. The major advantage of the signal processing approach is that it may cost less and the existing LR imaging systems can be still utilized. The SR image reconstruction is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including medical imaging, satellite imaging, and video applications. The goal of this article is to introduce the concept of SR algorithms to readers who are unfamiliar with this area and to provide a review for experts. To this purpose, we present the technical review of various existing SR methodologies which are often employed. Before presenting the review of existing SR algorithms, we first model the LR image acquisition process.IEEE Signal Processing Magazine 06/2003; · 4.48 Impact Factor