Luxin Yan

Title: Luxin Yan: Innovator in Image Processing Technologies

Introduction

Luxin Yan is a prominent inventor based in Hubei, China. He has made significant contributions to the field of image processing, particularly in the estimation of blur kernels. With a total of 4 patents to his name, Yan's work addresses critical challenges in image deblurring algorithms.

Latest Patents

One of Yan's latest patents is titled "Method and system for selecting image region that facilitates blur kernel estimation." This invention discloses a method for selecting an image region that aids in blur kernel estimation. The process involves calculating a relative total variation value for each pixel in a blurred image, setting a threshold to identify boundary pixels, and sampling the image to obtain patches for analysis. This method effectively resolves issues related to operator dependency and efficiency in existing region selection methods.

Another notable patent is the "Method and system for estimating blur kernel size." This method includes pre-processing a blurred image to meet the input size requirements of a multi-class convolutional neural network (CNN). The image is then input into a trained CNN to generate a blur-kernel-size probability distribution vector. The estimated blur kernel size corresponds to the largest element in this vector, providing a systematic approach to blur kernel size estimation.

Career Highlights

Luxin Yan is affiliated with Huazhong University of Science and Technology, where he continues to advance research in image processing technologies. His innovative methods have garnered attention in both academic and practical applications.

Collaborations

Yan has collaborated with notable colleagues, including Nong Sang and Lerenhan Li, who contribute to his research endeavors. Their combined expertise enhances the development of cutting-edge solutions in image processing.

Conclusion

Luxin Yan's contributions to image processing through his innovative patents demonstrate his commitment to advancing technology in this field. His work not only addresses existing challenges but also paves the way for future developments in image deblurring algorithms.