Essential Image Processing for Magnetic-Resonance Force Microscopy

Two fundamental challenges face development of the magnetic-resonance force microscope (MRFM): sensitivity and image deconvolution. Because of the non-local nature of the MRFM response to a single spin, image processing of as-captured MRFM data will be socritical a component of the instrument that its performance will have a profound impact on the entire system design. In this Phase I STTR project, Pixon LLC will combine the MRFM hardware research efforts at Ohio State University and the CaliforniaInstitute of Technology with the company's proprietary, high-performance image-reconstruction technology in order to demonstrate unmatched capabilities in MRFM imaging. In particular, compared to the best competing techniques, the Pixon method of imagereconstruction offers 2 to 3 times better resolution and 10 to 100 times better sensitivity. At the same time, the information-theoretic principles that underlie the Pixon algorithm make its performance effectively impossible to surpass. In short, thisproject will establish absolute limits on MRFM imaging capabilities and make specific recommendations for MRFM hardware design that optimize the benefit of Pixon post processing. BENEFITS: Optimizes sensitivity and spatial resolution of the MRFM.APPLICATIONS: Image processing for MRFM, MFM, and potentially all microscopies.