Traditional HDR capture has mostly relied on merging images captured with different exposure times. While this works well for static scenes, dynamic scenes poses difficult challenges as registration of differently exposed images often leads to ghosting and other artifacts. This chapter reviews methods which capture HDR-video frames within a single exposure time, using either multiple synchronised sensors, or by multiplexing of the sensor response spatially across the sensor. Most previous HDR reconstruction methods perform demoisaicing, noise reduction, resampling (registration), and HDR-fusion in separate steps. This chapter presents a framework for unified HDR-reconstruction, including all steps in the traditional imaging pipeline in a single adaptive filtering operation, and describes an image formation model and a sensor noise model applicable to both single-, and multi-sensor systems. The benefits of using raw data directly are demonstrated with examples using input data from multiple synchronized sensors, and single images with varying per-pixel gain.