Compression of Microarray Images Using Spatial Redundancy

Microarray image technology is a powerful tool for monitoring thousands of genes simultaneously. The size of microarray images is very large; hence efficient compression routines that take advantage of the way in which spots are represented in a microarray image are required. In this paper we introduce an image compression method that aims to minimize the number of pixels to be stored, to represent a spot. The compressed data is then used to reconstruct the microarray. The reconstructed array is then compared with the original image to determine the deviation between the two. The results of the implementation of this method are compared with other image compression methods and higher compression ratio is obtained. The reconstructed image has low ischolar_main mean square error value which can be further reduced by subtracting the background.