Researchers are exploring new methods for image compression and enhancement in biological microscopy, including the use of implicit neural image fields and deep-learning-based solutions. Various frameworks and techniques are being developed, such as sparsity-efficient models and semantic redundancy-aware compression, to improve the processing of multidimensional biomedical image data. These advancements may be related to or complement other emerging technologies in microscopy, including adaptive-learning physics-assisted light-field microscopy and correlative microscopy methods.