No abstract

Reconstruction of high resolution images from multiple low resolution images at various displacements is a well studied, ill posed problem. Designs using lenses with different imaging characteristics improve the theoretical results and also reduce the image reconstruction problem to a set of loosely coupled smaller reconstructions. This paper derives the performance limits for reconstruction from multiple lower resolution images as a function of measurement bit precision and measurement noise.

We present results of an on-going project to assess the applicability in reflection seismology of emerging super resolution techniques pioneered in digital photography. Our approach involves: (1) construction of a forward model connecting low resolution seismic images to high resolution ones, and (2) solution of a Tikhonov-regularized ill conditioned optimization problem to construct a high resolution image from several lower resolution counterparts; the high and low resolution images derived, respectively, from dense and sparse seismic surveys.