High-Speed Restoration of Atomic Force Microscopy Images Using Tikhonov Regularization in GPGPU

The Atomic Force Microscopy (AFM) is a scanning probe technique widely used to produce nanometric scaled images of virtually any kind of non-conductive or biological surface. Depending on the scanning dimensions an expected AFM image structure is subjected to be modified by great amounts of external noise (low Signal/Noise ratios) - electrical or mechanical - and/or blurring due to the geometry of the measuring probe. In order to minimize such effects, image restoration techniques can be employed. The one based on the minimization of the Tikhonov´s regularization functional is described, taking into account the characteristics of the measuring probe and the S/N ratio. This work proposes optimizations on both serial and parallel restoration algorithms, using CUDA library on a General Purpose Graphics Processing Unit, GPGPU, in terms of time performance and quality of restoration in regime of high speed imaging, one frame/sec or more. The results obtained are so far very promising, reaching speedups up to 43x over previous implementations.