AIMS: To improve visualisation of angiographic features in patients with age related macular degeneration associated with choroidal neovascularisation (CNV) and related complications. To evaluate if image averaging can achieve this goal. METHODS: 27 eyes of 20 sequential patients with age related macular degeneration over a 3 month period were studied. Indocyanine green angiograms (ICGA), fluorescein angiograms (FA), and oral fluorescein angiograms were recorded with a confocal scanning laser ophthalmoscope. Software was used to average multiple images from a 10-20 image series (over 0.5-1.0 seconds). Image quality was assessed by two masked observers and graded on a scale of 0-3. A more quantifiable grading method was devised by adding a variable amount of Gaussian noise to the improved image until the original and image averaged image appeared equal. RESULTS: Masked review showed mild to strong improvement of visualisation of structures including borders of CNV. Improvement varied depending on the type and phase of the angiogram. Improvement was highest in late phase FA, mid and late phase ICGA, and all phases of oral FA. CONCLUSION: Image averaging using software based algorithms improves the quality of angiographic images, particularly late ICGA images and oral FAs. This method may assist in the visualisation of choroidal neovascularisation in age related macular degeneration.