In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement
algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a
cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be
enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron
microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the
original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive
contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be
implemented and utilized as a comparison tool to evaluate the performance of our algorithm.