This chapter addresses the main aspects of computational bioimaging applied to the microscopy of living organisms. It explains the current context of microscopy imaging, and presents the most notable operations of image processing and image analysis of microscopy under the dual umbrella of model-based and data-driven approaches. The chapter provides the general principles underlying algorithms and the terms used in the field allowing for more in-depth research. Image formation in fluorescence microscopy follows the physical laws of light propagation that can be mathematically modeled by a convolution between the emitted light signal and the point-spread function to which noise is added. In order to guarantee reliable statistics in life sciences, it is essential to acquire a large number of images, which requires automating image analysis. The chapter concludes with a perspective on the challenges of microscopy image processing and analysis.