ﻻ يوجد ملخص باللغة العربية
For ghost imaging, pursuing high resolution images and short acquisition times required for reconstructing images are always two main goals. We report an image reconstruction algorithm called compressive sampling (CS) reconstruction to recover ghost images. By CS reconstruction, ghost imaging with both super-resolution and a good signal-to-noise ratio can be obtained via short acquisition times. Both effect influencing and approaches further improving the resolution of ghost images via CS reconstruction, relationship between ghost imaging and CS theory are also discussed.
Much more image details can be resolved by improving the systems imaging resolution and enhancing the resolution beyond the systems Rayleigh diffraction limit is generally called super-resolution. By combining the sparse prior property of images with
Based on compressive sampling techniques and short exposure imaging, super-resolution imaging with thermal light is experimentally demonstrated exploiting the sparse prior property of images for standard conventional imaging system. Differences betwe
Both ghost imaging (GI) and ghost imaging via compressive sampling (GICS) can nonlocally image an object. We report the influence of spatial transverse coherence property of a thermal source on GI and GICS and show that, using the same acquisition nu
Mid-wave infrared (MWIR) cameras for large number pixels are extremely expensive compared with their counterparts in visible light, thus, super-resolution imaging (SRI) for MWIR by increasing imaging pixels has always been a research hotspot in recen
As one of important analysis tools, microscopes with high spatial resolution are indispensable for scientific research and medical diagnosis, and much attention is always focused on the improvement of resolution. Over the past decade, a novel techniq