Picture processing techniques

Abstract

Image processing techniques find applications in many areas, chief among which are image enhancement, picture compression, pattern recognition, efficient picture coding and image understanding. In this master thesis, some important aspects of image p[rocessing techniques which are listed below are discussed 1 - The mathematical models used in picture processing applications like fast unitary transforms, autoregressive and. state variable models, linear prediction models. Applications of these models in several image processing problems, including image restoration, smoothing, enhancement, data compression and detection. 2 - A large variety of iulage data compression and coding techniques. Some simple sampling and quantization techniques, Pulse Code Modulation (PCM), Differential PCM (DPCM), predictive coding and adaptive coding techniques. 3- Major edge detection techniques and alternative algorithms to the three different levels of edge detection schemes (preprocessing, labeling, postprocessing algorithms). In addition to the discussion of these three aspects, two package programs have been developed to simulate data compression and edge detection techniques by using a microcomputer. For evaluation of edge detection schemes, some qualitative and quantitative performance criteria are generated and comparison of three edge detection schemes ts also done due to these criteria.