Radar shadow detection in SAR images using DEM and projections
원문 초록
Synthetic aperture radar (SAR) images are widely used in target recognition tasks nowadays. In this letter, we propose an automatic approach for radar shadow detection and extraction from SAR images utilizing geometric projections along with the digital elevation model (DEM) which corresponds to the given geo-referenced SAR image. First, the DEM is rotated into the radar geometry so that each row would match that of a radar line of sight. Next, we extract the shadow regions by processing row by row until the image is covered fully. We test the proposed shadow detection approach on different DEMs and a simulated 1D signals and 2D hills and volleys modeled by various variance based Gaussian functions. Experimental results indicate the proposed algorithm produces good results in detecting shadows in SAR images with high resolution.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Reflectance Based Method For Shadow Detection and Removal
Direction-aware Spatial Context Features for Shadow Detection
A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation
When SAM2 Meets Video Shadow and Mirror Detection
Unveiling Deep Shadows: A Survey and Benchmark on Image and Video Shadow Detection, Removal, and Generation in the Deep Learning Era
RenDetNet: Weakly-supervised Shadow Detection with Shadow Caster Verification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.