Identification and Classification of Phenomena in Multispectral Satellite Imagery Using a New Image Smoother Method and its Applications in Environmental Remote Sensing
원문 초록
In this paper a new method of image smoothing for satellite imagery and its applications in environmental remote sensing are presented. This method is based on the global gradient minimization over the whole image. With respect to the image discrete identity, the continuous minimization problem is discretized. Using the finite difference numerical method of differentiation, a simple yet efficient 5*5-pixel template is derived. Convolution of the derived template with the image in different bands results in the discrimination of various image elements. This method is extremely fast, besides being highly precise. A case study is presented for the northern Iran, covering parts of the Caspian Sea. Comparison of the method with the usual Laplacian template reveals that it is more capable of distinguishing phenomena in the image.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Fast Isotropic Median Filtering
A Complementary Global and Local Knowledge Network for Ultrasound denoising with Fine-grained Refinement
Difference of Anisotropic and Isotropic TV for Segmentation under Blur and Poisson Noise
Contrastive Semantic-Guided Image Smoothing Network
A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
Field of Junctions: Extracting Boundary Structure at Low SNR
토론
이 논문과 연결된 포럼 글이 아직 없습니다.