Digital Mammogram is widely accepted as a common modality of breast cancer detection. Image enhancement techniques play a significant role in subjectively altering the brightness and contrast of an image. These methods, despite the reported merits, suffer from over-enhancement, which has adverse effect in segmentation as well as feature extraction. This paper presents a new enhancement algorithm that enhances a digital mammogram, based on the iterative partition of its histogram pattern. The proposed Modified-Dualistic Sub-Image Histogram Equalization (M-DSIHE) method primarily partitions the original histogram into two, using the mid-point of the active dynamic intensity range of the input image. Then the partitioned histograms are iteratively divided and the histogram equalization is applied on the each partitioned histogram. This M-DSIHE has the advantage of enhancing the contrast of the original image, with due brightness preservation. The recorded results of the M-DSIHE method is observed to have an edge over the competitive methods, in terms of the quantitative and qualitative metrics.

Mammogram enhancement, Histogram, Histogram Equalization, Contrast Enhancement, Mammogram Segmentation, DSIHE

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