Adaptive noise reduction filtering on moving scanned-electron microscope images

In this paper, a number of different image processing algorithms have been applied in order to improve the appearance of an image to the human eye and to achieve a noise reduction. The algorithms were applied to a single fixed image and also to a sequence of images which contained motion. Histogram equalization as described offers a more interesting method of enhancing images than other histogram manipulation operators. That is why the nonlinear mapping function, to re-assign values in the output histogram, offers more possibilities to alter the original shape of the histogram into a desired shape. This method improves the appearance of an image to the human eye, more than a measurable mathematical factor such as the noise reduction factor. Recursive filtering is an important tool to reduce noise on images. The great advantage of recursive filtering is that the realization is not very complicated and the expenditure is relatively small. To obtain certain transfer functions, only a few changes in the programmed algorithms are necessary to provide the user with the desired filter characteristics. The adapted motion technique uses a recursive filter as well and allows one to run a sequence of images without smearing effects and with a high performance in noise reduction.