New infrared blur estimation and restoration algorithm

This paper presents a systematic new methodology for restoration of infrared images. The approaches described herein are applicable to single frame and multi-frame or hyper-spectra infrared images. The restoration problem is performed in two stages: (1) noise reduction and (2) linear blur and image estimation and restoration. The additive and multiplicative noise reduction is statistically optimal and improves the estimation of blurring function and restored image. For the restoration process we discuss alternate methods and provide the framework for error free restoration by eliminating the well known singularity problems that are often present in inverse solutions with singularities. Some initial results are presented.