With the evolution of automated computing systems Bio-Medical image analysis is made simple. Leukemia is a malignant disease (Cancer) seen in people of any age groups either in children or adults aged over 50 years. The microscopic images usually inadequate to identify the type of the cell in most of the cases, the traditional morphology test done by a hematologist to look under the microscope is a time consuming and tedious job. Also the equipment required is very costly and may not be exist in all hospitals and clinics. Further the noises and blurness effect often leads to false diagnosis of leukemia. An automatic image enhancement and segmentation system can make the inspection procedure of leukocytes much easier and faster and the amount of data that can be analyzed by such a clinician handle more data than they normally can handle. In this paper four contrast enhancement techniques are implemented for analysis of blood cancer. A comparative approach is done on Local contrast stretching, Global contrast stretching, Dark contrast stretching, Bright contrast stretching methods. All these methods involve threshold mapping which often useful to attain segmented results.

Index Terms: Electron micrograph image enhancement, Acute leukemia, local contrast, global contrast, dark, bright contrast stretching.