鍏抽敭璇�: WorldView-2鍗槦閬ユ劅褰卞儚, 鐗¤泿鍏绘畺鍖�, 褰卞儚铻嶅悎

Abstract: Image fusion is one of the most important steps in remote sensing information extraction.To select the appropriate fusion method is the crucial link.In this paper锛孹iangshan Port in Zhejiang Province is the study area锛宎nd the oyster culture is the observation target.The satellite of WorldView-2 multispectral and panchromatic images were used to detect the distribution of the coastal oyster farming.The different five fusion methods锛宻uch as Principal Component Analysis (PCA)锛孏ram-Schmidt(GS)锛孨NDiffuse Pan Sharpening锛孊rovey Transform and Wavelet Transform锛寃ere evaluated by two of subjective qualitative and objective quantitative aspects.We compared the fused images with the original image using six kinds of statistical parameters including mean锛宻tandard deviation锛宔ntropy锛宎verage grads锛宑orrelation coefficient and spectral distortion to evaluate the images’ fusion performance.The results indicate that锛宖or the characteristics of coastal oyster farming锛宼he fusion image by principal component analysis method not only preserves detail spatial texture information but also maintains the spectral character well.The method of PCA is the most suitable fusion method for remote sensing applications in coastal oyster culture with WorldView-2 images.The fusion effect of GS is second to PCA锛寃hich can be used as an alternate method for fusion applications.NNDiffuse Pan Sharpening锛學avelet transform and Brovey transform are inappropriate for the identification and extraction of oyster culture floating raft.

Key words: WorldView-2 image, Oyster culture area, Image fusion