光声成像,在光学混浊介质中具有潜在光学分辨率的声学成像模态,引起了极大的关注。然而,计算光声成像中波前优化和光栅扫描的收敛导致了快速映射的挑战,特别是对于接近声学深亚波长范围的空间分辨率。作为稀疏采样范例,压缩感知已应用于许多领域,以加速数据采集,而不会造成明显的质量损失。在这项工作中,我们提出了一种用于光声表面层析成像的双压缩方法,该方法可以在混浊环境中实现3D空间分辨率不受声学限制的高效成像。双压缩光声成像与单像素检测,通过具有同步时间光声编码的空间光学调制,即使在原始光声信号的方差较弱时,也允许从调制的声信号解码精细光学信息。我们进行了双压缩光声成像的原理证明数值演示,这解决了声学亚声波长的细节,大大减少了测量次数,揭示了动态成像的潜力。双重压缩概念,将不显眼的空间差异转化为时空可检测信息,可以推广到其他成像模式以实现高效,高空间分辨率成像。
Photoacoustic imaging, an acoustic imaging modality with potentially optical resolution in an optical turbid medium, has attracted great attention. However, the convergence of wavefront optimization and raster scanning in computational photoacoustic imaging leads to the challenge of fast mapping, especially for a spatial resolution approaching the acoustic deep-subwavelength regime. As a sparse sampling paradigm, compressive sensing has been applied in numerous fields to accelerate data acquisition without significant quality losses. In this work, we propose a dual-compressed approach for photoacoustic surface tomography that enables high-efficiency imaging with 3D spatial resolution unlimited by the acoustics in a turbid environment. The dual-compressed photoacoustic imaging with single-pixel detection, enabled by spatially optical modulation with synchronized temporally photoacoustic coding, allows decoding of the fine optical information from the modulated acoustic signal even when the variance of original photoacoustic signals is weak. We perform a proof-of-principle numerical demonstration of dual-compressed photoacoustic imaging, that resolves acoustic sub-acoustic-wavelength details with a significantly reduced number of measurements, revealing the potential for dynamic imaging. The dual-compressed concept, which transforms unobtrusive spatial difference into spatio-temporal detectable information, can be generalized to other imaging modalities to realize efficient, high-spatial-resolution imaging.