This work reports and illustrates the application of enhancement techniques to animal nervous system images from a Laser Scanning Confocal Microscope. Images obtained from this equipment are used to help researchers on localizing several organelles and proteins. Different image components of the same tissue sample can be acquired varying the confocal microscope laser beam wavelength. Due to non-ideal acquisition, numerous images contain artifacts, poor distribution of gray levels and unsystematic contrast gradient. Several techniques have been implemented in order to enhance the images, including noise and artifacts reduction, contrast expansion and enhancements on organelles borders, such as emboss and 3D-visualization. A methodology to accurately solve the frequent contrast gradient problem has been implemented. The approach is based on blurring filter, histogram equalization and arithmetic operations. Image coloring is another issue. Each of the acquired components must be merged into one single image with its respective color. The final phase of the work consisted of gathering all implemented techniques to elaborate an application that enclosed facilities to automatically open files from confocal file format (.pic format), apply the developed methodologies to enhance the images, build the multi-component artificial color image and save the results in common formats. This application must deal with large amounts of images easily, providing facilities to batch processing and image indexing and labeling.