REVIEW OF VARIOUS HISTOGRAM BASED MEDICAL IMAGE ENHANCEMENT TECHNIQUES

Image enhancement is a processing on an image to make it more suitable for some applications. The main problem addressed by this paper is the enhancement of medical images using efficient algorithms based on HE techniques. The paper involves analyzing and formulating different HE image enhancement techniques suitable for various medical applications. More precisely, proposed research will focus on the enhancement of medical images captured under poor illumination conditions, foggy situations and speckle noise etc.,. Developing algorithms that would assist doctors to diagnose the disease in the beginning stage only. For example the removal of speckle noise and artifacts with segmenting kidney from those images where kidney boundary are not much clear. Medical images are enhanced using efficient Histogram Equalization(HE) techniques such as Iterative dynamic HE, Dualistic sub-image HE, Background brightness preserving HE, Gray-level and gradient magnitude HE. For improving the performance of image processing systems the crucial solution is implementation of image processing techniques in hardware. Therefore for improving the performance of image processing systems, for flexible design development, more compact, low power, and high speed and to reduce cost and time, gives the implementation of efficient histogram algorithms on Field Programmable Gate Array (FPGA).