Particle Swarm Optimization based Contrast Limited enhancement for mammogram images

In the present medical scenario detection of breast cancer in its early stage is a very immense challenge. Many histogram based enhancement are present today. In this paper a Particle Swarm Optimization (PSO) for tuning the enhancement parameter of Contrast Limited Adaptive Histogram Equalization (CLAHE) based on Local Contrast Modification (LCM) is presented. The PSO method of parameter tuning adopted for LCM-CLAHE enhancement for mammogram images achieves very good quality of images compared to other exiting methods. The quality of enhanced image is tested using an efficient objective criteria based on entropy and edge information of the image. Results are compared with other enhancement techniques such as histogram equalization, unsharpmasking. The performance of this method is tested using Peak Signal to Noise Ratio. The quality of image shows that image obtained after this method can be useful for efficient detection of breast cancer in further process like segmentation, classification etc.