Company Filing History:
Years Active: 2021-2025
Title: Innovations of Jason G. Valentine
Introduction
Jason G. Valentine is a prominent inventor based in Nashville, TN (US). He has made significant contributions to the field of optics, particularly in the development of advanced imaging systems. With a total of four patents to his name, his work is paving the way for new technologies in optical image processing.
Latest Patents
One of his latest patents is focused on flat optics for image differentiation. This invention features a 2D spatial differentiator that operates in transmission and comprises a silicon nanorod photonic crystal. It transforms an image into its second-order derivative, allowing for direct discrimination of edges within the image. The use of a 2D photonic crystal enables differentiation and edge detection in all directions, achieving a numerical aperture (NA) of up to 0.315 and an experimental resolution smaller than 4 μm. This nanophotonic differentiator can be directly integrated into optical microscopes and camera sensors, demonstrating its versatility in existing imaging systems. Furthermore, integration with a metalens has been shown to create a compact and monolithic image-processing system. Overall, this innovation significantly reduces the size compared to traditional systems, opening new avenues for optical analog image processing in applications related to computer vision.
Career Highlights
Jason G. Valentine is affiliated with Vanderbilt University, where he continues to push the boundaries of optical technology. His research focuses on integrating nanophotonic devices into practical applications, enhancing the capabilities of imaging systems.
Collaborations
Some of his notable coworkers include You Zhou and Hanyu Zheng, who contribute to the innovative research environment at Vanderbilt University.
Conclusion
Jason G. Valentine is a leading figure in the field of optics, with groundbreaking patents that enhance imaging technologies. His work not only advances scientific understanding but also has practical implications for various applications in computer vision.