This paper proposes a multiple pitch estimation algorithm for the piano music which improves both precision and processing time. The conventional method applies non-negative matrix factorization (NMF) and singular value decomposition to ensure the continuity of sound and pattern of musics. However, audio signal spectrogram has large elements and processing singular value decomposition is inefficient in the computational time. Our method separates the input audio spectrogram into the block of sound. Then we apply a NMF with group sparsity constraint to enforce the continuity of sound. In addition, we use the different dictionaries for the attack part and the reverberation part of the sound. It improves the precision of the estimation for each part.