title: Moderated histogram equalization, an automatic means of enhancing the contrast in digital light micrographs reversibly.
abstract: A means for improving the contrast in the images produced from digital light micrographs is described that requires no intervention by the experimenter: zero-order, scaling, tonally independent, moderated histogram equalization. It is based upon histogram equalization, which often results in digital light micrographs that contain regions that appear to be saturated, negatively biased or very grainy. Here a non-decreasing monotonic function is introduced into the process, which moderates the changes in contrast that are generated. This method is highly effective for all three of the main types of contrast found in digital light micrography: bright objects viewed against a dark background, e.g. fluorescence and dark-ground or dark-field image data sets; bright and dark objects sets against a grey background, e.g. image data sets collected with phase or Nomarski differential interference contrast optics; and darker objects set against a light background, e.g. views of absorbing specimens. Moreover, it is demonstrated that there is a single fixed moderating function, whose actions are independent of the number of elements of image data, which works well with all types of digital light micrographs, including multimodal or multidimensional image data sets. The use of this fixed function is very robust as the appearance of the final image is not altered discernibly when it is applied repeatedly to an image data set. Consequently, moderated histogram equalization can be applied to digital light micrographs as a push-button solution, thereby eliminating biases that those undertaking the processing might have introduced during manual processing. Finally, moderated histogram equalization yields a mapping function and so, through the use of look-up tables, indexes or palettes, the information present in the original data file can be preserved while an image with the improved contrast is displayed on the monitor screen.
authors.affiliation: The Ludwig Institute for Cancer Research, 91, Riding House Street, London W1W 7BS, UK. alane@ludwig.ucl.ac.uk
authors.forename: A
authors.initials: A
authors.lastname: Entwistle
mesh_terms: D000199:Actins / Q000378:metabolism; D000957:Antigens, Viral, Tumor / Q000378:metabolism; D002478:Cells, Cultured; D042783:Endothelial Cells; D005904:Glial Fibrillary Acidic Protein / Q000378:metabolism; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D018613:Microscopy, Confocal; D009457:Neuroglia / Q000378:metabolism / Q000648:ultrastructure; D011467:Prostate; D014404:Tubulin / Q000378:metabolism; D014407:Tumor Cells, Cultured; D014471:Umbilical Veins / Q000166:cytology
chemical_list: D000199:Actins; D000957:Antigens, Viral, Tumor; D005904:Glial Fibrillary Acidic Protein; D014404:Tubulin