Increase the Intelligibility of Multispectral Image Using Pan-Sharpening Techniques for Many Remotely Sensed Images

Ibn Al-Haitham Journal for Pure and Applied Sciences

关键词: Images pan sharpening, Ehlers, Gram-Schmidt, wavelet, local variance matching.;   

DOI  :  

来源: DOAJ

【 摘 要 】

 Pan sharpening (fusion image) is the procedure of merging suitable information from two or more images into a single image. The image fusion techniques allow the combination of different information sources to improve the quality of image and increase its utility for a particular application. In this research, six pan-sharpening method have been implemented between the panchromatic and multispectral images, these methods include Ehlers, color normalize, Gram-Schmidt, local mean and variance matching, Daubechies of rank two and Symlets of rank four  wavelet transform. Two images captured by two different sensors such as landsat-8 and world view-2 have been adopted to achieve the fusion purpose. Different fidelity metric like MSE, RMSE, PSNR, Cc, ERGAS and RASE have been used to achieve the comparison among the fusion methods. The results show that Daubechies wavelet (db2) transform was good method for pan sharpening images. Where good statistical values have been obtained, when it is applied on the first and second image that are captured by different sensors with different spatial resolution

【 授权许可】

Unknown