International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Cellular Automata Technology in Scalable Color Image Coding

Author : Lilly Raffy Cheerotha, ¹ Ameefa P K ²

Date of Publication :18th July 2019

Abstract: A scalable color image coding algorithm is a multi resolution representation of the data. It can be often obtained using a linear filter bank. Reversible cellular automata have been proposed recently as simpler, nonlinear filter banks that produce a similar representation. The original image is decomposed into four sub bands, such that one of them retains most of the features of the original image at a reduced scale. The project discusses the utilization of reversible cellular automata and arithmetic coding for scalable compression of color images. In the binary case, the proposed algorithm that uses simple local rules compares well with the JBIG compression standard, in particular for images where the foreground is made of a simple connected region. For complex images, more efficient local rules based upon the lifting principle have been designed. They provide compression performances very close to or even better than JBIG, depending upon the image characteristics. In the gray scale case, and in particular for smooth images such as depth maps, the proposed algorithm outperforms both the JBIG standards under most coding conditions. In color images after sampling equally optimal transform per component could be computed. Cellular automata transform is a new scheme to enhance resolution in terms of compression ratio.

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