The presentation of mixtures not only influences the performance of image classification and target recognition

but also is an obstacle to quantitative analysis of remote sensing images.Therefore

a novel spectrum filter based fully constrained mixture analysis algorithm is proposed in this paper to tackle this problem.The spectrum filter

which could wipe off the background spectrum in a mixed pixel

is firstly proposed to obtain the sum-to-one constrained fractional abundance of mixtures in remote sensing images.Since the precise endmember set of a mixture can be obtained by continually modifying the endmember space when minus abundance exists

the spectrum filter based iterative algorithm is present to realize fully constrained mixture analysis.Experimental analysis based on synthetic multispectral data set demonstrates that the proposed algorithm obviously outperforms the popular Fully Constrained Least Square unmixing（FCLS） algorithm and the Orthogonal Subspace Projection （OSP） algorithm.In addition

the proposed algorithm also achieves very promising performance on real hyperspectral images.