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In order to evaluate growth status of maize automatically and accurately, a multi-spectral image camera was used to collect ground-based images of maize canopy in the field. The average gray value (GIA, RIA and NIRIA) and the vegetation indices (DVI, RVI, NDVI, et al.) widely used in remote sensing were selected as the parameters for maize growth monitoring. The parameters were obtained based on image...
This letter presents a novel synthetic aperture radar (SAR) image segmentation method based on a single graph cut. Due to the speckle, the classical pixel-by-pixel Markov random field (MRF) based SAR image segmentation method may still result in salt and pepper label map. Compared to the classical MRF based SAR image segmentation method, our proposed method exploits geometric prior to describe the...
The paper proposes a fast and accurate semantic segmentation approach for a large Polarimetric SAR (PolSAR) image using Conditional Random Fields (CRFs). It efficiently incorporates the polarimetric signatures, texture and intensity features into a unite CRFs model, and employs a fast max-margin training method for parameters learning. Experiments on RadarSat-2 PolSAR data in Flevoland test site demonstrate...
Flood is one of the most common and expensive natural disaster. Rapid and efficient procedure to accurately detect the flood-inundated area irrespective of weather conditions will help the monitoring and rescuing during the seasonal flooding period. In this paper, a procedure is proposed to obtain the flood mapping using multi-temporal TerraSAR-X data. And a comparative experiment is design to test...
A Turbo iterative method for signal processing is proposed. This method is a kind of multi-systems collaborative signal processing through iteration: several independent systems work in rotation, and each system takes feedback information from the other systems as a priori condition. We have applied such a Turbo iterative signal processing (TISP) method on speech signal enhancement, and on SAR (synthetic...
The new method of active fortify organizing a supervised area based on color and geometric feature is proposed in this paper. By the basis of color feature in the real supervised scene, in the first instance extracting several regions of interest (ROI) with noise, then matching with geometric shape by Fourier descriptors in the database, sequentially achieving automatic organizing a supervised area...
In this paper, we propose a modified segmentation algorithm based on level set for synthetic aperture radar (SAR) images. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. One main drawback of previous the SAR image segmentation algorithm based on active contour model and level set is the computational expense...
A fast approach to obtain segmentation of SAR images has been suggested here based on the local statistical characteristics using Markov random field (MRF) model on region adjacency graph (RAG). First, an initially over-segmented image derived from the watershed segmentation algorithm as well as the original SAR image is taken as the inputs of the proposed method. Secondly, a MRF is defined on RAG...
In this paper, a novel approach for change detection in multitemporal synthetic aperture radar (SAR) images is presented. The proposed approach based on region likelihood ratio feature detection exploits an edge fusion technique for the SAR images segmentation. Segmentation is the key process in change detection based on region feature and the proposed edge fusion technique of two segmentation images...
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