  One of the common algorithms used to reconstruct photoacoustic (PA) images is
the non-adaptive Delay-and-Sum (DAS) beamformer. However, the quality of the
reconstructed PA images obtained by DAS is not satisfying due to its high level
of sidelobes and wide mainlobe. In contrast, adaptive beamformers, such as
minimum variance (MV), result in an improved image compared to DAS. In this
paper, a novel beamforming method, called Double MV (D-MV) is proposed to
enhance the image quality compared to the MV. It is shown that there is a
summation procedure between the weighted subarrays in the output of the MV
beamformer. This summation can be interpreted as the non-adaptive DAS
beamformer. It is proposed to replace the existing DAS with the MV algorithm to
reduce the contribution of the off-axis signals caused by the DAS beamformer
between the weighted subarrays. The numerical results show that the proposed
technique improves the full-width-half-maximum (FWHM) and signal-to-noise ratio
(SNR) for about 28.83 \mu m and 4.8 dB in average, respectively, compared to MV
beamformer. Also, quantitative evaluation of the experimental results indicates
that the proposed D-MV leads to 0.15 mm and 1.96 dB improvement in FWHM and
SNR, in comparison with MV beamformer.
