Abstract: Examples include imaging one or more objects contained inside a droplet. A method includes generating at least one hologram of the one or more objects contained in the droplet by using in-line lens-free imaging. The at least one hologram includes at least one artifact that is caused by the droplet and that affects the at least one characteristic of the one or more objects contained in the droplet. The method includes at least partially removing the at least one artifact or the cause of the at least one artifact. The method further includes generating an image, after or during removing the at least one artifact or the cause of the at least one artifact. The image includes the one or more objects. The method also comprises recognizing the at least one characteristic of the one or more objects based on the image.

Abstract: A method for three-dimensional imaging of a sample (302) comprises: receiving (102) interference patterns (208) acquired using light-detecting elements (212), wherein each interference pattern (208) is formed by scattered light from the sample (302) and non-scattered light from a light source (206; 306), wherein the interference patterns (208) are acquired using different angles between the sample (302) and the light source (206; 306); performing digital holographic reconstruction applying an iterative algorithm to change a three-dimensional scattering potential of the sample (302) to improve a difference between the received interference patterns (208) and predicted interference patterns based on the three-dimensional scattering potential; wherein the iterative algorithm reduces a sum of a data fidelity term and a non-differentiable regularization term and wherein the iterative algorithm includes a forward-backward splitting method alternating between forward gradient descent (108) on the data fidelity term

Abstract: A method for three-dimensional imaging of a sample (302) comprises: receiving (102) interference patterns (208) acquired using light-detecting elements (212), wherein each interference pattern (208) is formed by scattered light from the sample (302) and non-scattered light from a light source (206; 306), wherein the interference patterns (208) are acquired using different angles between the sample (302) and the light source (206; 306); performing digital holographic reconstruction applying an iterative algorithm to change a three-dimensional scattering potential of the sample (302) to improve a difference between the received interference patterns (208) and predicted interference patterns based on the three-dimensional scattering potential; wherein the iterative algorithm reduces a sum of a data fidelity term and a non-differentiable regularization term and wherein the iterative algorithm includes a forward-backward splitting method alternating between forward gradient descent (108) on the data fidelity term