Efficient coding of morphology based multiresolution pyramids

The present paper discusses an approach of efficient coding of the error inlages obtained using the morphology based multiresolution pyramid decomposition technique proposed by Heijmans and Toet. A commonly used approach to achieve significant compression ratios in pyramid compression techniques is to discard the first error image. However, this may cause degradation of fine edges, texture information, and thin features. In the present paper we have proposed an estimator for the first error image. Directional filtering and sampling are used to decompose the error image into two components. The error image can be accurately (but not exactly) reconstructed from these two components. The two image components have lesser entropy than the original error image. Specific properties of these image components may be exploited to achieve higher compression. For various standard images (Lenna, Baboon, Peppers, and Airplane) we observed that the bits per pixel required to code the first error image can be reduced by 35 to 40 percent to obtain "near lossless" compression with the help of the proposed estimator. Texture information and edges were restored very accurately. Starting from the low resolution image resulting from the omission of the first error image. the present technique was observed to reduce the Mean Square Error (MSE) by approximately 90 percent for the above mentioned standard images.