The fundamental principles of quantization and the two basic types of quantization techniques-scalar and vector-have been introduced. The concept of VQ, its salient features, design of code book, and advantages/disadvantages has been dealt with in detail. VQ is a data compression technique, producing a reconstruction with as small a distortion as possible. The quality of the reconstruction depends on the amount of data that is discarded. The performance of different classes of VQ techniques like structured and unstructured VQ, memory and memoryless VQ, the types of VQ under each of these categories have been discussed. This article has surveyed these to a certain extent, and much more remains if a detailed analysis is required

Contrast enhancement is an important issue in the field of mammographic image processing. It can be classified into two categories: direct contrast enhancement and in direct contrast enhancement. Indirect contrast enhancement involves in modifying histogram of the image. Histogram equalization (HE) is the simplest indirect contrast enhancement technique which is widely used for contrast enhancement. Many variants of HE are proposed so far. Comparison of these techniques is significantly essential in deciding a suitable algorithm for enhancement and further processing. In this paper we applied few indirect contrast enhancement techniques namely histogram equalization, CLAHE, BBHE, RMSHE, MMBEBHE to preprocess the mammographic images. The performance of the methods is measured using effective measure of enhancement (EME) and peak signal to noise ratio (PSNR)