  This paper deals with the theory and application of 2-Dimensional,
nine-neighborhood, null- boundary, uniform as well as hybrid Cellular Automata
(2D CA) linear rules in image processing. These rules are classified into nine
groups depending upon the number of neighboring cells influences the cell under
consideration. All the Uniform rules have been found to be rendering multiple
copies of a given image depending on the groups to which they belong where as
Hybrid rules are also shown to be characterizing the phenomena of zooming in,
zooming out, thickening and thinning of a given image. Further, using hybrid CA
rules a new searching algorithm is developed called Sweepers algorithm which is
found to be applicable to simulate many inter disciplinary research areas like
migration of organisms towards a single point destination, Single Attractor and
Multiple Attractor Cellular Automata Theory, Pattern Classification and
Clustering Problem, Image compression, Encryption and Decryption problems,
Density Classification problem etc.
