Abstract: A method of detecting red-eye features (1) in a digital image comprises identifying highlight regions (2) of the image having pixels with a substantially red hue and higher saturation and lightness values than pixels in the regions therearound. In addition, pupil regions (3) comprising two saturation peaks either side of a saturation trough may be identified. It is then determined whether each highlight or pupil region corresponds to part of a red-eye feature on the basis of further selection criteria, which may include determining whether there is an isolated, substantially circular area (43) of correctable pixels around a reference pixel. Correction of red-eye features involves reducing the lightness and/or saturation of some or all of the pixels in the red-eye feature.

Abstract: A method of correcting red-eye features in a digital image includes generating a list of possible features by scanning through each pixel in the image searching for saturation and/or lightness profiles characteristic of red-eye features. For each feature in the list, an attempt is made to find an isolated area of correctable pixels which could correspond to a red-eye feature. Each successful attempt is recorded in a list of areas. Each area is then analysed to calculate statistics and record properties of that area, and validated using the calculated statistics and properties to determine whether or not that area is caused by red-eye. Areas not caused by red-eye and overlapping areas are removed from the list. Each area remaining is corrected to reduce the effect of red-eye. More than one type of feature may be identified in the initial search for features.