CEC366-Image Processing


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Image Processing (IP) 

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      Santhosh (Admin) 
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UNIT -1 
1. Image sampiing and quantization
2. DFT SUMS **
3. Color model **
UNIT-2
1. Histogram equalization (sum)**
2.gray level information transformation, image smoothening methods rare
3..Butterworth and Gaussian filters, Homomorphic filter**
UNIT-3
1. Image restoration technique
2. Wiener filter ,statistics filter, adaptive filter**rare band pass filters
unit 4
1. Region based segmentation
2.Dam construction, Watershed segmentation algorithm**
3.Edge detection, Edge linking via Hough transform**

UNIT-5
1. Two boundary representation**
1. Huffman code (baby)**
3. Shift ,Arithmetic code ,jpeg
PART-C
1.Compulsory Questions {a case study where the student will have to read and analyse the subject }
A. May be a sum so study all algorithm properly to get good scores
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Syllabus
UNIT I DIGITAL IMAGE FUNDAMENTALS
Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Relationships between pixels - Color image fundamentals - RGB, HSI models, Two-dimensional mathematical preliminaries, 2D transforms - DFT, DCT.
UNIT II IMAGE ENHANCEMENT     
Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering– Smoothing and Sharpening Spatial Filtering, Frequency Domain: Introduction to Fourier Transform– Smoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian filters, Homomorphic filtering, Color image enhancement.
UNIT III IMAGE RESTORATION     
Image Restoration - degradation model, Properties, Noise models – Mean Filters – Order Statistics – Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering
UNIT IV IMAGE SEGMENTATION     
Edge detection, Edge linking via Hough transform – Thresholding - Region based segmentation – Region growing – Region splitting and merging – Morphological processing- erosion and dilation, Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed segmentation algorithm.
UNIT V IMAGE COMPRESSION AND RECOGNITION
Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, JPEG standard, MPEG. Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture - Patterns and Pattern classes - Recognition based on matching.

UNIT 1:DIGITAL IMAGE FUNDAMENTALS

Steps in digital image processing-components-elements of visual perception-image sensing and acquisition-image sampling and quantization-relation ship between pixels-colour image fundamentals-RGB,HSI models,two-dimensional mathematical preliminaries,2D tranforms-DFT,DCT.

UNIT:2 IMAGE ENHANCEMENT

Spatial domain:grey level transformation-histogram processing-basics of spatial filtering-smoothing and sharpening spatial filtering,frequency domain:introduction to fourier transform-smoothing and sharpening frequency domain filters-ideal,Butterworth and Gaussian filters,homorphic filtering,color imag enhancement.

UNIT 3:IMAGE RESTORATION

Image restoration-degradation model,properties,noise models-mean filter-order statistics-adaptive filters-band reject filters-band pass filter-notch filters-optimum notch filtering-inverse filtering-wiener filtering.

UNIT 4:IMAGE SEGMENTATION 

Edge detection,edge linking via hough transform-thresholding -region based segmentation-region growing-region splittinga and merging -morphological processing-erosion and dilation,segmentation by morphological watersheds-basic concepts-dam construction -watershed segmentation algorithm

UNIT 5:IMAGE PROCESSING AND RECOGNITION

Need for data compression,huffman,run length encoding,shift codes,arithmetic coding,JPEG standard,MPEG.Boundary representation,fourier descriptor,regional descriptor-topological features,texture-patterns and pattern classes-recognition based on matching

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