Wavefront shaping with a Hadamard basis for highly scattering soil imaging

Soil is a highly scattering media that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex and opaque media of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets, which are optimized sequentially. Simulation and experimental optimization results demonstrate our method has a ~7 times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.