Image compression is used to reduce the number of bits required to represent an image or video sequence. A compression algorithm takes input X and generates compressed information that requires fewer bits. The decompression algorithm reconstructs the compressed information and gives the original. Medical image compression is an important area of ​​biomedical and telemedicine. In medical application, image study and data compression are developing rapidly with increasing applications, including teleradiology, biomedical, telemedicine. Medical image compression and image analysis of the data could be even more useful and can play a main role in diagnosing more complicated and difficult images through expert consultation [2]. In the field of medical image compression, diagnosis and analysis simply work when compression techniques protect all key image information needed for storage and transmission, known as zero-touch compression. loss. the other scheme is that lossy compression is more efficient in terms of storage and transmission requirements, but there is no guarantee of preserving the information in the characteristics necessary for medical diagnosis. To avoid the above problem, it is diagnostically important that image transmission and storage be losslessly compressed. . Region of interest (ROI) is a very useful segmentation approach for diagnostic purposes. These regions of interest must be compressed by a lossless or near-lossless compression algorithm. Wavelet-based techniques are the most recent growth in the field of medical image compression.2. EXISTING METHOD: Region of interest is an important feature provided by the jpeg 2000 standard. The entire image is encoded as a single entity by different fidelity constraints. This...... middle of paper ...... The lossless compression method includes stroke length coding and LZW (Lempel Ziv Welch). This method provides lossy compression scheme rather than lossless compression scheme because in lossy compression technique it provides better compression ratio compared to lossless scheme. Step 5: Integer multi-wavelet transformation IMWT is proposed for the implementation of a multi-wavelet system based on a multi-scalar function. .Step 6: Decompressed ImageIn this decompression process, the encoded binary data which is compressed can be extracted.4. RESULTS: Original image is taken as attestation image of size 256 CONCLUSION: In this paper, the focus is on implementing a lossless image data codec, when the input image data is encrypted.