Compressive-uniform hybrid sensing for image acquisition and communication
We propose a new image acquisition and recovery strategy of hybrid sensing (HS) that combines random sampling of compressive sensing (CS) and uniform down sampling. HS lets the two sampling schemes complement each other so that one can have the best of both worlds: signal-independent sparse sampling that is the hallmark of CS, and locally adaptive signal reconstruction that is afforded by uniform sampling. We suggest a few important applications of HS in image acquisition and communication, such as multispectral imaging, multiple description image coding, multiview video, and ultra-high throughput imaging (e.g., functional medical imaging).