Digital Image Processing DIP Pune University by Prashant Badgujar, Manoj Nagmode
DIGITAL IMAGE PROCESSING For Graduate & Post-Graduate Courses in EngineeringUseful for Pune University and Other Universities AUTHORSDR. MANOJ .S. NAGMODE MR. PRASHANT N. BADGUJAR M.E., Ph. D. (E & TC), Ph.D. (Pursuing in H.R.D.);Prof. in E & TC Department, M.B.A. (I.B.M, H.R.M); SAP ABAPM.I.T. College of Engineering, Consultant, B.E. (Electronics)Kothrud, Pune – 411038 Gazetted Officer (D.T.E.), Govt. Polytechnic, Ahmednagar–414001 PRANJAL PUBLICATION
ACKNOWLEDGEMENT I Mr. Prashant N. Badgujar take opportunity to thank Prof. Dr. Manoj S. Nagmode ofM.I.T. College Of Engineering, Kothrud, Pune and also to my family for ValuableGuidance, Encouragement and Support in making this book a reality. Any constructive comments, suggestion from students and colleagues forimprovement of the book will be highly appreciated and gratefully acknowledged. Youcan write your queries, suggestions and your problems on the email@example.com PREFACE The tremendous power and usefulness of Digital Image Processing can be seen from thedifferent fields like remote sensing via satellite, Image transmission and storage, Medicalprocessing, Radar, SONAR, Robotics, Missile systems for weapon design, Astronomy, Automatedinspection of industrial parts / components, Geographical mapping etc. The areas of Digital Imageprocessing have been increasing day by day, resulting in an unprecedented interest in the subject. This text book is useful for students of final year degree courses in Electronics / Electronicsand Telecommunication / Computer / Instrumentation Engineering of Pune University. This book isalso useful for M.E./ M.Tech. and other Universities in Maharashtra & India. This book gives theoretical and practical knowledge of Digital Image Processing. This bookwill prove to be very useful for students. The students have to omit nothing and possiblyhave to cover nothing more. The book prepares very carefully a background of each topic withessential illustrations, practical examples, salved problems and important questions from previousuniversity question papers. Each chapter is supported with sufficient number of problems and clearrepresentation of complex diagrams, which are the distinguishing features of this book. The bookcovers everything the students need to familiarize themselves with Digital Image Processing. Thechapters in the book are arranged in proper sequence as per university syllabus, which is importantin understanding the subject in easier ways. This book is organized into eight units. Unit – 1 gives general introduction and basic concepts in Digital Image Processing. Unit – 2 introduces all techniques used for Image Enhancement to improve overall quality of an image and Color Image Fundamentals. Unit – 3 deals with various Digital Image Transforms used in Digital Image Processing. Unit – 4 deals with compression techniques to remove different types of redundancies in an image. Also JPEG / MPEG standards & Use of Fractals for image compression is introduced in this chapter. Unit – 5 introduces Morphological Operations to be carried out on images. Unit – 6 deals with various restoration techniques for images which are corrupted due to noise. Also some of Digital Image Processing applications are introduced briefly. Unit – 7 deals with wavelets and compression using wavelets Unit – 8 deals with quantization and few basic concepts from image processing. – AUTHORS
SYLLABUSB.E. (ELECTRONICS & TELECOMMUNICATIONS) 2008 COURSE–P.U. UNIT 1 DIGITAL IMAGE FUNDAMENTALS : Components of Image Processing System. , Elements of Visual Perception, MTF of Visual System, Image Sensing and Acquisition, Image formation model, Image Sampling & Quantization Spatial and Gray Level Resolution, Basic Relationships between Pixels. Statistical parameters, Measures and their significance, Mean, standard deviation, variance, SNR, PSNR etc. UNIT 2 DIGITAL IMAGE ENHANCEMENT & COLOR IMAGE FUNDAMENTALS: Enhancement in Spatial Domain: basic gray level transformations, histogram processing, equalization, Arithmetic and logical operations between images, Basics of spatial filtering, smoothening and sharpening spatial filters. Image Enhancement in frequency Domain: smoothening and sharpening frequency domain filters. Fundamental of color image processing: color models, RGB, CMY, YIQ, HIS. Pseudo Color Image processing: Intensity filtering, gray level to color transformation, Basics of full color image processing. UNIT 3 DIGITAL IMAGE TRANSFORMS : 2D-DFT, FFT, DCT, the KL Transform, Walsh/Hadamard Transform, Haar Transform UNIT 4 DIGITAL IMAGE CODING AND COMPRESSION : Image Coding Fundamentals, Image Compression Model, fundamentals- redundancy: coding, interpixel, psychovisual, fidelity criteria, elements of information theory. Error Free Compression - variable length, bit plane, Lossless Predictive, Lossy Compression- Lossy Predictive. Fundamentals of JPEG, MPEG, fractals. UNIT 5 IMAGE ANALYSIS : Edge detection, spatial feature and boundary extraction, boundary representation by chain codes and B splines, Hough Transform. Morphological Image Processing: Dilation, Erosion, Opening, Closing on Binary Images, Segmentation: Point, line. Edge detection, Boundary detection and Thersholding. UNIT 6 IMAGE RESTORATION AND IMAGE PROCESSING APPLICATIONS : Image Degradation Mode, Noise Models, and Restoration in Presence of Noise in spatial Domain, Linear Filtering, Applications: Character Recognition, Fingerprint Recognition, Remote Sensing. Applications using different Imaging modalities such as acoustic Imaging, Medical imaging, electron microscopy etc.
SYLLABUS B.E. (COMPUTER ENGINEERING) 2008 COURSE–P.U.UNIT 1 What is digital image processing? Origin, usage and application of imageprocessing. Fundamental steps and component of image processing system.Introduction to Human Visual System. Digital representation of images(monochrome & color). Elements of matrix theory, Digital Imaging Hardware &Software.UNIT 2 Basic image preprocessing (contrast enhancement, simple noisereduction, color balancing), Spatial transformation Gray Level liner and non-linear transformation, Histogram Processing, Hadamard and Walshtransformation. Image enhancement in spatial and frequency domain: basicfundamental, smoothing and sharpening domain filters. Sampling & Quantization.UNIT 3 Image Processing filters, Image Segmentation & Analysis,Implementation Feature extraction: Edges, Lines & corners detection, Texture &shape measures. Segmentation & thresholding, region extraction, edge (Canny) ®ion based approach, use of motion in segmentation. Feature extraction- Edges,Lines & corners detection, Texture & shape measures.UNIT 4: Image Restoration & Reconstruction.Introduction, Model of Image degradation, Noise Models, Classification of imagerestoration techniques, Blind-deconvolution techniques, Lucy RichardsonFiltering, Wiener Filtering.UNIT 5 Image Compression & Object Recognition.Introduction to Image Compression and its need, Coding Redundancy,Classification of Compression Techniques (Lossy and Losless - JPEG, RLE,Huffman, Shannon fano), Scalar & Vector Quantization. Introduction to ObjectRecognition, Object Representation (Signatures, Boundary Skeleton), SimpleBoundary Descriptors, Regional descriptors(Texture).UNIT 6 Wavelets & Application of Image Processing.Background: Image pyramids, Sub-band coding, Haar and Daubechies Wavelets.Image Compression using Wavelets (JPEG 2000). Principal Component Analysis& Local Component Analysis for dimension reduction.
SYLLABUS B.E. (ELECTRONICS ENGINEERING) 2008 COURSE–P.U.Unit 1: Introduction to image processing Image Processing Applications, Fundamental steps in Digital image processing, Elements of visual perception, Image sensing and acquisition, Basic Concepts in Sampling and Quantization, representing digital images.Unit 2: Image Enhancement Some basic gray level transformations, Histogram Processing, Arithmetic Operations, Spatial filtering, Smoothing and Sharpening Spatial filters, Image Enhancement in the Frequency Domain, Gaussian filters, Homomorphic filtering.Unit 3: Image Segmentation Some Basic Relationships between pixels, point, line and edge detection, Gradient operators, Canny edge detection, pyramid edge detection. Edge linking and boundary detection, Hough transform, Chain codes, boundary segments, skeletons, Boundary descriptors, Fourier descriptors. Thresholding, global thresholding, adaptive thresholding, use of boundary characteristics for histogram improvement and local thresholding, Region based segmentation, Region growing, region splitting and merging.Unit 4: Image Compression Data redundancies Elements of information, variable-length coding, predictive coding, Transform coding, Image compression standards, Wavelets and Multiresolution processing Image pyramids, subband coding.Unit 5: Representation and Description Shape Representation and Description, Region Identification, Contour based shape representation and description, Region based representation and description, Shape classesUnit 6: Object Recognition and 3 D vision Statistical pattern recognition and Syntactic pattern recognition, Graph Matching, 3 D vision and Geometry, Single perspective camera , scene reconstruction from multiple views.
SYLLABUS B.E. (INSTRUMENTATION ENGINEERING) 2008 COURSE–P.U.Unit- 1: Introduction to Digital Image Processing Digital image representation, fundamental steps in image processing, elements of digital image processing systems, hardware for image processing system, Characteristics of image digitizer, Types of digitizer, Image digitizing components, Electronic image tube cameras, solid state cameras, scanners.Unit- 2: Fundamentals of Digital Image Processing Elements of visual perception, a simple image model sampling and quantization some basic relationship between pixels, image geometry, Basic transformations, Perspective transformation, Camera model and calibration, stereo imaging.Unit- 3: Image Transforms 2-D Fourier transform, Discrete cosine transform, Short time Fourier transform, Gabor transform, Radon transform.Unit- 4: Image Enhancement Enhancement by point processing, spatial filtering, enhancement in the frequency domain. Contrast intensification: linear stretching, non-linear stretching, Histogram specification, low contrast stretching. Smoothing: Image averaging, mean filter, order statistics filter, edge preserving smoothing. Sharpening: High pass filtering, homomorphic filtering. Introduction to color image processingUnit- 5: Image Restoration Degradation model, diagonalization of circulate and block-circulate matrices, algebraic approach to restoration, inverse filtering, least mean square (wiener) filter, constrained least squared restoration, invractive restoration.Unit- 6: Image Analysis Segmentation: detection of discontinuities, edge linking and boundary detection, thresholding, region -oriented segmentation, Representation and description: Representation schemes, descriptors, regional descriptors, pattern and pattern classes, Classifiers. Edge Detection: derivative operators: Sobel, Prewittt, Canny, second order derivative, line detection.