苏科华
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
E-Mail:
Date of Employment:2008-11-02
School/Department:计算机学院
Education Level:研究生毕业
Business Address:D203
Gender:Male
Contact Information:13517299596
Status:Employed
Discipline:Computer Applications Technology
Communications and Information Systems
Other specialties in Software Engineering
Cyberspace Security
Hits:
Impact Factor:1.7
DOI number:10.1117/1.JRS.10.015009
Affiliation of Author(s):SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Journal:JOURNAL OF APPLIED REMOTE SENSING
Place of Publication:1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98225
Key Words:disparity compensation;rate-distortion optimization;image compression;stereo image coding;three-line-scanner image coding
Abstract:Disparity compensation (DC) and transform coding are incorporated into a hybrid coding to reduce the code-rate of multiview images. However, occlusion and inaccurate disparity estimations (DE) impair the performance of DC, especially in spaceborne images. This paper proposes an adaptive disparity-compensation scheme for the compression of spaceborne multiview images, including stereo image pairs and three-line-scanner images. DC with adaptive loop filter is used to remove redundancy between reference images and target images and a wavelet-based coding method is used to encode reference images and residue images. In occlusion regions, the DC efficiency may be poor because no interview correlation exists. A rate-distortion optimization method is thus designed to select the best prediction mode for local regions. Experimental results show that the proposed scheme can provide significant coding gain compared with some other similar coding schemes, and the time complexity is also competitive. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Co-author:Jia Liming
First Author:Li Shigao
Indexed by:Article
Correspondence Author:Su Kehua
Document Type:J
Volume:10
Issue:1
ISSN No.:1931-3195
Translation or Not:no
Date of Publication:2016-03-09
Included Journals:SCI、EI
苏科华,男,武汉大学计算机学院教授、博导;武汉大学科技成果转化中心(技术转移中心)副主任。研究主要集中在最优传输(Optimal Transport)领域,它是研究概率测度间最优变换的一类优化问题。在计算机图形学、机器视觉、人工智能、医学图像处理等领域有着广泛的应用。本人主要研究最优传输的几何计算理论和高效算法,并将其应用于网格保测参数化、三维场景优化、智能烧伤评估和卫星互联网任务优化中。主持包括国家自然科学基金、中央军科委、航天5院、华为公司等20多个项目支持,发表论文50余篇,获批发明专利10余项。为CCF计算机辅助设计与图形学(CAD/CG)和虚拟现实与可视化(TCVRV)专委会的执行委员。