Contemporary data compression is used extensively for image and video transmission and storage purposes for the reduction of transmission bandwidth requirement, power requirement, and storage requirement. The main issue for the development of Lossless Image Compression systems is to manipulate the one Image model to another while keeping the total information preserved. For lossless Image Compression the model transformation should be reversible as well as Probabilistic in nature in order to reduce the bit rate, preserve energy and exact recovery of Image after decompression. Efficient representation of image under any model depends on total energy distribution of components and the entropy of such model. Entropy has close relation with energy distribution of different image or data components hence with compression performance. It is achievable better compression performance (Low Bit Rate) over the existing transform compression systems if selected suitable model having favourable energy distribution. Out proposed colour image compression system is achieving better performance with respect to Signal to Noise Ratio and Compression Ratio directly related to Retained Energy and Number of Zeros in transformed coefficients.

Colour Space, Colour Image Compression, Redundancy, Entropy