Resolution enhancement of video sequences with adaptively weighted low-resolution images and simultaneous estimation of the regularization parameter

In many imaging systems, the resolution of the detector array of the camera is not sufficiently high for a particular application. Furthermore, the capturing process introduces additive noise and the point spread function of the lens and the effects of the finite size of the photo-detectors further degrade the acquired video frames. The goal of resolution enhancement is to estimate a high-resolution image from a sequence of low-resolution images while also compensating for the degradations. We propose a technique for image resolution enhancement with adaptively weighted low-resolution images (channels) and simultaneous estimation of the regularization parameter. The weight coefficients work as the cross-channel fidelity to each low-resolution image, while the regularization parameter acts as the within-channel balance between data and prior model for each channel. Experimental results are presented and conclusions are drawn.