J. Levman, J. Alirezaie, and G. Khan (Canada)
Histogram equalization, image enhancement, medical image processing
In this paper, we present a novel technique for histogram equalization. Histogram equalization (or flattening) is the process of redistributing an input image's grey level values to produce an output image easily analyzed by the human eye. Histogram equalization is primarily utilized in image enhancement. Most of the existing approaches to histogram flattening employ a simple transformation function that defines the resultant grey level value for any given input. We propose a multi-stage histogram equalization algorithm that guarantees a perfectly flat output histogram. Our algorithm consists of three stages, each of which creates an intermediate image. Results have shown that our approach to histogram equalization can result in excellent image enhancement. The benefits of such an algorithm are particularly important in medical applications such as x-ray images.
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