Human Visual System based Processing for High Resolution Remote Sensing Image Segmentation
Image segmentation is very essential and critical to image processing and pattern recognition. Watershed is the most popular one among all the proposed image segmentation algoritbms, but it suffers from over-segmentation. To resolve the over-segmentation problem and obtain a concise region representation has been the focus of many researchers. There are many ways to reduce the over-segmentation However, Human visual system (HVS) is often not incorporated into the consideration and process of segmentation.This paper presents a new approach to high resolution remote sensing image segmentation taking into consideration human visual system (HVS) model. A Contrast Sensitivity Function (CSF) based filtering is applied to the image before watershed trAnsform. Multi-scale spatial frequency filtering images are derived from setting multi-scale viewing distance. Then the region merging based on Just Noticeable Difference (JND) is applied to the segmentation results. Finally, the efffect of reducing over segmentation based on CSF and JND is analyzed and significant improvement is reported in the experimental results.
human visual system CSF muki-scale filtering JND watershed transform
Guizhou Wang Guojin He
Center for Earth Observation and Digital Earth Chinese Academy of Sciences Graduate University of Ch Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing, China
国际会议
2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)
大连
英文
474-478
2010-07-05（万方平台首次上网日期，不代表论文的发表时间）