Super resolution with superposition
نویسندگان
چکیده
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 manufacturers have been moving to evershorter wavelengths and thus need to solve the challenges associated with use of extreme ultraviolet light. These include the lack of cheaply available optical elements that operate at such short wavelengths, and the damaging effects such high-energy photons have on the imaging elements and the photoresist. Nearly ten years ago, a quantum optical approach to imaging—quantum imaging, which uses path-entangled states—was suggested as a solution for this requirement of ever-shorter wavelengths and a way to beat the classical limit [2]. This turned out to be easier said than done. While quantum lithography is viewed as one of the “killer apps” for the nascent field of quantum imaging, the bugaboo in its implementation has been the continued lack of the right kind of multiphoton photoresists that would operate at the low flux levels required for a real proof-of-principle experiment.
منابع مشابه
Spectral Super-Resolution by Understanding Superposition Principle and Detecting Processes
We present analytical and experimental results demonstrating a conceptual break through on how to overcome the fundamental timefrequency bandwidth limit (or spectral superresolution) for a light pulse in traditional and heterodyne spectrometry. This can be achieved either by a de-convolution process suggested by analytical method or by heterodyne method, which we demonstrate.
متن کاملSuper-Resolution from Noisy Data
This paper studies the recovery of a superposition of point sources from noisy bandlimited data.In the fewest possible words, we only have information about the spectrum of an object in the low-frequency band[−flo, flo] and seek to obtain a higher resolution estimate by extrapolating the spectrumup to a frequency fhi > flo. We show that as long as the sources are separated b...
متن کاملSuper-resolution of Defocus Blurred Images
Super-resolution is a process that combines information from some low-resolution images in order to produce an image with higher resolution. In most of the previous related work, the blurriness that is associated with low resolution images is assumed to be due to the integral effect of the acquisition device’s image sensor. However, in practice there are other sources of blurriness as well, inc...
متن کاملSupport detection in super-resolution
We study the problem of super-resolving a superposition of point sources from noisy low-pass data with a cut-off frequency fc. Solving a tractable convex program is shown to locate the elements of the support with high precision as long as they are separated by 2/fc and the noise level is small with respect to the amplitude of the signal.
متن کاملImproving Super-resolution Techniques via Employing Blurriness Information of the Image
Super-resolution (SR) is a technique that produces a high resolution (HR) image via employing a number of low resolution (LR) images from the same scene. One of the degradations that attenuates performance of the SR is the blurriness of the input LR images. In many previous works in the SR, the blurriness of the LR images is assumed to be due to the integral effect of the image sensor of the im...
متن کاملStable Separation and Super-Resolution of Mixture Models
We consider simultaneously identifying the membership and locations of point sources that are convolved with different band-limited point spread functions, from the observation of their superpositions. This problem arises in three-dimensional super-resolution single-molecule imaging, neural spike sorting, multi-user channel identification, among other applications. We propose a novel algorithm,...
متن کامل