JNTUK B.Tech Digital Image Processing for R13 Batch.

JNTUK B.Tech Digital Image Processing gives you detail information of Digital Image Processing R13 syllabus It will be help full to understand you complete curriculum of the year.

OBJECTIVES
The student will

• Learn the fundamental concepts and applications of Digital Image Processing.
• Learn the concepts of and how to perform Intensity transformations and spatial filtering.
• Understand the relationship between Filtering in spatial and frequency domains,
• Understand the concepts of and how to perform Image restoration and reconstruction.
• Understand the concepts of different color models and Color image processing.
• Learn the concepts of Wavelets and multi-resolution processing, Image compression and Watermarking, Morphological image processing, Image segmentation, Representation and description.

UNIT-1 : Introduction: Origins of digital image processing, uses digital image processing, fundamental steps in digital image processing, components of an image processing system, digital image fundamentals, Elements of visual perception, light and electromagnetic spectrum, imaging sensing and acquisition, image sampling and quantization. Some basic relationships between pixels, an introduction to the mathematical tools used in digital image processing.

Image Transforms: Need for image transforms, Spatial Frequencies in image processing, introduction to Fourier transform, discrete Fourier transform, fast Fourier transform and its algorithm, properties of Fourier transform. Discrete sine transforms. Walsh Transform. Hadamard transform, Haar Transform. Slant transforms, SVD and KL Transforms or Hotelling Transform

UNIT-2 : Intensity Transformations and Spatial Filtering: Background, Some basic intensity transformation functions, histogram processing, fundamentals of spatial filtering, smoothing spatial filters, sharpening spatial filters, Combining spatial enhancement methods, using fuzzy techniques for intensity transformations and spatial filtering.

Filtering in the frequency domain: Preliminary concepts, Sampling and the Fourier transform of sampled functions, the discrete Fourier transform (DFT) of one variable, Extension to functions of two variables, some properties of the 2-D Discrete Fourier transform. The Basic of filtering in the frequency domain, image smoothing using frequency domain filters, Selective filtering, Implementation.

UNIT-3 : Image restoration and Reconstruction: A model of the image degradation / Restoration process, Noise models, restoration in the presence of noise only- Spatial Filtering, Periodic Noise Reduction by frequency domain filtering, Linear, Position –Invariant Degradations, Estimation the degradation function, Inverse filtering, Minimum mean square error(Wiener) filtering ,constrained least squares filtering ,geometric mean filtering ,image reconstruction from projections

Unit-4 : Color image processing: color fundamentals, color models, pseudo color image processing, basic of full color image processing, color transformations, smoothing and sharpening. Image segmentation based on color, noise in color images, color image compression.

Unit-5 : Wavelets and Multi-resolution Processing: image pyramids, sub band coding & Haar transforms multi resolution expressions, wavelet transforms in one dimensions. The fast wavelets transform, wavelet transforms in two dimensions, wavelet packets. Image compression: Fundamentals, various compression methods-coding techniques, digital image water marking.

Unit-6 : Morphological image processing: preliminaries Erosion and dilation, opening and closing, the Hit-or-miss transformation, some Basic Morphological algorithms, grey –scale morphology Image segmentation: Fundamentals, point, line, edge detection thresholding, region –based segmentation, segmentation using Morphological watersheds, the use of motion in segmentation.

TEXT BOOKS

• R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd edition, Prentice Hall, 2008.
• R. C. Gonzalez, R. E. Woods and Steven L. Eddins , Digital Image Processing Using MATLAB , 2rd edition, Prentice Hall, 2009.
• Anil K.Jain, “Fundamentals of Digital Image Processing”, Prentice Hall of India, 9th Edition,
• Jayaraman, S. Esakkirajan, and T. Veerakumar, Digital Image Processing, Tata McGraw-Hill Education, 2011.

OUTCOMES
After going through this course the student will be able to

• Perform different transforms on image useful for image processing applications
• Perform spatial and frequency domain filtering on image and can implement all smoothing and sharpening operations on images
• Perform image restoration operations/techniques on images
• Operate effectively on color images and different color conversions on images and can code images to achieve good compression
• Do wavelet based image processing and image compression using wavelets Perform all morphological operations on images and can be able to do image segmentation also.
• Develop simple algorithms for image processing and use the various techniques involved in Bio Medical applications, etc.

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