  In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is
delay-and-sum (DAS) due to its simple implementation. However, it results in a
low quality image affected by the high level of sidelobes. Coherence factor
(CF) can be used to address the sidelobes in the reconstructed images by DAS,
but the resolution improvement is not good enough compared to the high
resolution beamformers such as minimum variance (MV). As a weighting algorithm
in linear-array PAI, it was proposed to use high-resolution-CF (HRCF) weighting
technique in which MV is used instead of the existing DAS in the formula of the
conventional CF. The higher performance of HRCF was proved numerically and
experimentally. The quantitative results obtained with the simulations show
that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves
the full-width-half-maximum of about 91 % and 15 % and the signal-to-noise
ratio about 40 % and 14 %, respectively. Moreover, the contrast ratio at the
depth of 20 mm has been improved about 62 % and 21 % by HRCF, compared to
DAS+CF and MV+CF, respectively
