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We propose a cell detection algorithm using non-negative matrix factorization (NMF) on Ca²⁺ imaging data. To apply NMF to Ca²⁺ imaging data, we use the bleaching line of the background fluorescence intensity as an a priori background constraint to make the NMF uniquely dissociate the background component from the image data. This constraint helps us to incorporate the effect of dye-bleaching and reduce the non-uniqueness of the solution. We demonstrate that in the case of noisy data, the NMF algorithm can detect cells more accurately than Mukamel’s independent component analysis algorithm, a state-of-art method. We then apply the NMF algorithm to Ca²⁺ imaging data recorded on the local activities of subcellular structures of multiple cells in a wide area. We show that our method can decompose rapid transient components corresponding to somas and dendrites of many neurons, and furthermore …