The purpose of sparse unmixing (SU) is to find the optimal spectral subset from library and uses this model each pixel in hyperspectral data. existing SU methods concern Gaussian noise a lot focus less on varied intensity different bands other types noise, e.g., impulse deadlines. Besides, high coherence limits performance SU. Given aforementioned problems, article proposes new method, called b...