A NOVEL REMOVAL METHOD FOR DENSE STRIPES IN REMOTE SENSING IMAGES
- 1School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
- 2School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
- 3LIESMARS, Wuhan University, Wuhan 430079, China
- 4School of Urban Design, Wuhan University, Wuhan 430072, China
- 5Collaborative Innovation Center for Geospatial Information Technology, Wuhan 430079, China
Keywords: Destriping, Remote sensing image, Savitzky–Golay (SG) filter, Optimization-based model, Alternating direction method of multipliers (ADMM)
Abstract. In remote sensing images, the common existing stripe noise always severely affects the imaging quality and limits the related subsequent application, especially when it is with high density. To well process the dense striped data and ensure a reliable solution, we construct a statistical property based constraint in our proposed model and use it to control the whole destriping process. The alternating direction method of multipliers (ADMM) is applied in this work to solve and accelerate the model optimization. Experimental results on real data with different kinds of dense stripe noise demonstrate the effectiveness of the proposed method in terms of both qualitative and quantitative perspectives.