  Delay and sum (DAS) is the most common beamforming algorithm in linear-array
photoacoustic imaging (PAI) as a result of its simple implementation. However,
it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS)
was used to address the incapabilities of DAS, providing a higher image
quality. However, the resolution improvement is not well enough compared to
eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer
has been combined with DMAS algebra, called EIBMV-DMAS, using the expansion of
DMAS algorithm. The proposed method is used as the reconstruction algorithm in
linear-array PAI. EIBMV-DMAS is experimentally evaluated where the quantitative
and qualitative results show that it outperforms DAS, DMAS and EIBMV. The
proposed method degrades the sidelobes for about 365 %, 221 % and 40 %,
compared to DAS, DMAS and EIBMV, respectively. Moreover, EIBMV-DMAS improves
the SNR about 158 %, 63 % and 20 %, respectively.
