Reconstructing Images of Two Adjacent Objects through Scattering Medium Using Generative Adversarial Network
This work addresses a specific challenge in multi-object scattering imaging for applications like medical image analysis, though it appears incremental as it extends existing single-object techniques to two objects.
The paper tackles the problem of reconstructing images of two adjacent objects through scattering media, which was previously limited to single objects, and demonstrates that their YGAN method can reconstruct both images from a single speckle pattern with high fidelity, even with additional scattering between objects.
Reconstruction of image by using convolutional neural networks (CNNs) has been vigorously studied in the last decade. Until now, there have being developed several techniques for imaging of a single object through scattering medium by using neural networks, however how to reconstruct images of more than one object simultaneously seems hard to realize. In this paper, we demonstrate an approach by using generative adversarial network (GAN) to reconstruct images of two adjacent objects through scattering media. We construct an imaging system for imaging of two adjacent objects behind the scattering media. In general, as the light field of two adjacent object images pass through the scattering slab, a speckle pattern is obtained. The designed adversarial network, which is called as YGAN, is employed to reconstruct the images simultaneously. It is shown that based on the trained YGAN, we can reconstruct images of two adjacent objects from one speckle pattern with high fidelity. In addition, we study the influence of the object image types, and the distance between the two adjacent objects on the fidelity of the reconstructed images. Moreover even if another scattering medium is inserted between the two objects, we can also reconstruct the images of two objects from a speckle with high quality. The technique presented in this work can be used for applications in areas of medical image analysis, such as medical image classification, segmentation, and studies of multi-object scattering imaging etc.