Comparison of Mean Field Annealing and Multiresolution Analysis in Missing Data Estimation

The project we are working on is to help develop and test a low cost, large area, high resolution X-ray detection system with a high dynamic range. The large area is achieved by butting two or more scintillator/fiber/CCD combinations together. An algorithm is thus required to compensate the defects come from the detector induced errors including missing single pixel due to individual defective detectors or missing column(s)/row(s) due to misalignment of adjacent CCD's in the blurred and noise corrupted images. Mean field annealing, as a global optimization technique, is the proposed algorithm. This paper, however, proposes a new approach based on multiresolution analysis where the defect compensation is implemented by removing the characteristics created by the missing columns/rows from the detail images of lower resolution. Experiments will be carried out to compare the performance of these two approaches. Future research directions are discussed at last.

• Type: Conference
• Year: 1998
• Where: ACCV
• Authors: Hairong Qi, Wesley E. Snyder, Griff L. Bilbro
• Keywords: ACCV 1998, Computer Vision, Detector Induced Errors, Large Area, Noise Corrupted Images