Classification of high resolution satellite images using spatial constraints-based fuzzy clustering

Abstract

A spatial constraints-based fuzzy clustering technique is introduced in the paper and the target application is classification of high resolution multispectral satellite images. This fuzzy-C-means (FCM) technique enhances the classification results with the help of a weighted membership function (W mf ). Initially, spatial fuzzy clustering (FC) is used to segment the targeted vegetation areas with the surrounding low vegetation areas, which include the information of spatial constraints (SCs). The performance of the FCM image segmentation is subject to appropriate initialization of W mf and SC. It is able to evolve directly from the initial segmentation by spatial fuzzy clustering. The controlling parameters in fuzziness of the FCM approach, W mf and SC, help to estimate the segmented road results, then the Stentiford thinning algorithm is used to estimate the road network from the classified results. Such improvements facilitate FCM method manipulation and lead to segmentation that is more robust. The results confirm its effectiveness for satellite image classification, which extracts useful information in suburban and urban areas. The proposed approach, spatial constraint-based fuzzy clustering with a weighted membership function (SCFCW mf ), has been used to extract the information of healthy trees with vegetation and shadows showing elevated features in satellite images. The performance values of quality assessment parameters show a good degree of accuracy for segmented roads using the proposed hybrid SCFCW mf -MO (morphological operations) approach which also occluded nonroad parts.Singh and Garg: Classification of high resolution satellite images using spatial constraints-based.

Road Detection from Remote Sensing Images using Impervious Surface Characteristics: Review and Implication

“…In the similar way, this kind of analysis is also carried out in the developed suburban and urban areas of the HRSI (Table 5). The overall values of quality assessment parameters are found higher (Singh and Garg, 2014b) in comparison to another (Singh and Garg, 2014a) Table 5. Performance evaluation of the road network extraction in different areas of HRSI…”

“…The controlling parameters have utilized in the fuzziness of the FCM approach, which help to estimate the segmented road results and thereafter Stentiford thinning algorithm (STA) is used to estimate the road network from classified results. Such improvements facilitate FCM method manipulation and lead to segmentation that is more robust (Singh and Garg, 2014a). The process of road extraction may be achieved in a single or multiple operations such as image segmentation (classification techniques), linear segments with constant width (Hough transform and edge detector), snakes (contour based object outlines), removing small blobs and merging relevant road segments (morphological operations), similarity with road templates, etc.…”

Một Cải Tiến Thuật Toán Kmeans Cho Việc Phân Vùng Ảnh Viễn Thám

“…Trong [7], Tao và cộng sự đề xuất một thuật toán phân đoạn ảnh vệ tinh dựa trên thuật toán phân cụm mờ có trọng số mới liên quan đến cửa sổ lân cận của các điểm ảnh. Ngoài ra, trong [8], Singh và các cộng sự cũng đề xuất thuật toán phân loại ảnh vệ tinh độ phân giải cao sử dụng phân cụm mờ dựa trên các ràng buộc phổ.…”

Analyzing the Saturation of Growing Stem Volume Based on ZY-3 Stereo and Multispectral Images in Planted Coniferous Forest

“…Although traditional field-based forest inventory can provide relatively accurate GSV in sample scale, the process is time-consuming and labor intensive, and in some cases, access to certain remoted forest areas is impossible [4]. At present, remote sensing (RS) technology is becoming an increasingly important tool for estimating GSV and resource assessment [5][6][7][8]. Over the last few decades, many variables related to forest GSV were extracted from optical remote sensing images with multi-spatial resolutions and multi-spectral sensors, such as Landsat series, Sentinel-2, GF series and ZY series satellites [9][10][11][12][13][14].…”