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Conversion of Region of Interest from One Block Size to Another in Compressed Domain

Image transforms are extensively used in image processing and image analysis. Transform is basically a mathematical tool, which allows us to move from one domain to another domain. Transforms play a significant role in various image processing applications such as image analysis, image enhancement, image filtering and image compression. Nowadays, almost all digital images are stored in compressed format in order to save the computational cost and memory. To save the memory cost, all the image processing techniques like feature extraction, image indexing and watermarking techniques are applied in the compressed domain itself rather than in spatial domain. In this paper, for compression purpose, Discrete Cosine Transform (DCT) is used because it has excellent energy compaction. The new approach devised in this paper is, if we will be able to find the relationship between the coefficients of a block to all of its sub-blocks in the DCT domain itself, without decompressing it so that time to extract global features in compressed domain for general image processing tasks will gets minimized. In this paper, composition of a block is obtained from all of its sub-blocks and vice versa directly in DCT domain also it is shown that the result of both operations are same. The computational complexity of the proposed algorithm is lower than that of the existing ones.