报告题目：A Novel Neural CSTV Model Joint with Quaternion-Based Group Sparse Representation for Color Image Inpainting from Structured Corruptions

报告人：江苏师范大学 贾志刚教授

报告时间：2026年8月10日 10:00-11:00

报告地点：体育赛事直播平台 106会议室

报告摘要：Most of color image restoration models overlook the valid information across color spaces and the coupling between color channels, which are essential properties. To address such limitations, we present a new two-stage image restoration model: Neural cross-space total variation regularization model with quaternion-based group sparse representation (QGS-NCSTV). In the first stage, a novel neural cross-space total variation regularization functional effectively captures the cross-space information to restore color images by incorporating the perceptual characteristics of the HSV space and the structural correlations of the RGB space. In the second stage, the quaternion-based group sparse representation preserves the coupling between color channels with leveraging nonlocal self-similarity. Experimental results show QGS-NCSTV outperforms the state-of-the-art methods in terms of PSNR, SSIM and UQI, where the reflection in colonoscopy images is successfully solved.

报告人简介：贾志刚，江苏师范大学数学与体育赛事直播 、数学研究院，教授、博导。2009年毕业于华东师范大学数学系，获理学博士学位；2023年入选江苏高校“青蓝工程”中青年学术带头人；2024年起担任学术期刊Numerical Algorithms的编委。主要研究方向为数值代数与图像处理，至今已在IEEE Trans. Image Process.，SIAM J. Matrix Anal. Appl., SIAM J. Sci. Comput., SIAM J. Imaging Sci. 等期刊上发表学术论文50余篇，其中 4 篇入选“ESI高被引”论文；在科学出版社（北京）出版英文专著1部（独立作者）；主持国家自然科学基金项目3项、省高校自然科学研究重大项目1项，参加国家自然科学基金重大项目和国家重点研发计划课题各1项。曾到英国曼彻斯特大学、香港浸会大学、澳门大学等高校数学系进行学术访问。