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In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm isdelay-and-sum (DAS) due to its simple implementation. However, it results in alow 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 highresolution beamformers such as minimum variance (MV). As a weighting algorithmin linear-array PAI, it was proposed to use high-resolution-CF (HRCF) weightingtechnique in which MV is used instead of the existing DAS in the formula of theconventional CF. The higher performance of HRCF was proved numerically andexperimentally. The quantitative results obtained with the simulations showthat at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improvesthe full-width-half-maximum of about 91 % and 15 % and the signal-to-noiseratio about 40 % and 14 %, respectively. Moreover, the contrast ratio at thedepth of 20 mm has been improved about 62 % and 21 % by HRCF, compared toDAS+CF and MV+CF, respectively

Image Improvement in Linear-Array Photoacoustic Imaging using High Resolution Coherence Factor Weighting Technique