The resolution of capacitive touch sensors is not sufficient for some sensing applications. The coarse resolution of a sensor with a regular grid is limited by the half distance between two adjacent layer-crossovers. Increasing the density of such layer-crossovers, improves the resolution of touch signals. While this technique needs some modification in the hardware, it does not necessarily guarantee that the corresponding estimated touch locations are more accurate. We explore the problem of resolution enhancement for the multitouch sensors here, using the sparsity pattern of the touch signals. This is called the super-resolution as the goal is to enhance the sensor resolution, while not changing the sensing hardware, and only incorporates some prior information about the input. The super-resolution problem can be computationally very costly. The aim is to present a rather simple algorithm to run in the real-time. This has been achieved by exploiting a structured sparse representation, which allows a computationally simple superresolution algorithm.