Image compression technique for biomedical image analysis has importance as because of time consuming process and also its storage . It becomes necessary to compress the image to reduce processing time required to retrieve target components from biomedical images. Also biomedical images requires more space for storage and also management of these images is very difficult. To compress the image, there are different techniques used. These techniques are classified in to lossy compression and lossless compression techniques. Out of these methods lossy compression schemes are not widely used due to possible loss of useful clinical information and as operations like enhancement may lead to further degradations in the lossy compression. While lossless schemes avoids above mentioned drawbacks of lossy compression technique. But no lossless compression algorithm can efficiently compress all possible data. For this reason, multiple algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain.