Enhancement of fluoroscopic images with varying contrast.
A heuristic algorithm for enhancement of fluoroscopic images of varying contrast is proposed. The new technique aims at identifying a suitable type of enhancement for different locations in an image. The estimation relies on simple preliminary classification of image parts into one of the following types: uniform, sharp (with sufficient contrast), detail-containing (structure present) and unknown (for the cases where it is difficult to make a decision). Different smoothing techniques are applied locally in the different types of image parts. For those parts that are classified as detail-containing, probable object boundaries are identified and local sharpening is carried out to increase the contrast at these places. The adopted approach attempts to improve the quality of an image by reducing available noise and simultaneously increasing the contrast at probable object boundaries without increasing the overall dynamic range. In addition, it allows noise to be cleaned, that at some locations is stronger than the fine structure at other locations, whilst preserving the details.
Ozanian
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Department of Computer Science, University of Hull, Hull HU6 7RX, UK.
Phillips
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D000465:Algorithms; D005471:Fluoroscopy / Q000379:methods* / Q000706:statistics & numerical data; D006620:Hip Fractures / Q000000981:diagnostic imaging; D006801:Humans; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*