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Mode Of Examination: Online
Number Of Question: 100 (1 Marks Each)
Total Time: 120 Min



Basic of Digital Image Processing:

Digital image processing introduction, steps and components.

Digital Image Fundamentals:

Image sampling and quantization, image sensing and acquisition, electromagnetic spectrum, relationship between pixels, mathematical tools of digital image processing.

Intensity Transformations and Spatial Filtering:

Smoothing and sharpening spatial filters, intensity transformation functions, spatial filtering and its fundamentals, spatial enhancement methods, histogram processing, smoothing linear and non-linear spatial filters, fuzzy techniques for intensity, transformation and filtering, unsharp masking, intensity transformation techniques, piecewise-linear transformation functions, noise reduction by spatial and domain filtering.

Filtering in Frequency Domain:

Frequency domain filtering basics, dft of one and two variables, fourier transform of sampled functions, image sharpening, smoothing and implementation, 2-d discrete fourier transform, sampling and selective filtering.

Image Restoration and Reconstruction:

Relationship between pixels, visual perception, adaptive filters, bandpass and band reject filters, geometric mean filters, inverse filters, notch and static filters, wiener filtering, fourier transform of functions and variables, noise restoration and reduction, least squares filtering and degradation function estimation.

Color Image Processing:

Color transformation and segmentation, full color and pseudo color image processing, image construction and formulation, color slicing and correction.

Image Compression:

Compression methods basics and fundamentals, bit plane and block transform coding, digital image watermarking, run length and symbol based coding, lossy and error free compression, image compression standards and models, multiresolution expansions and compression methods.

Morphological Image Processing:

Boundry extraction, complex hull, erosion and dilation, gray scale morphology, hit or miss transform, morphological reconstruction, skeletons and pruning, thinning and thickening, morphological algorithms, grey scale morphology applications.

Image Segmentation:

Edge detection, edge linking and boundary detection, line and point detection, thresholding and variable thresholding, image segmentation, segmentation using morphological watersheds and boundary segments..

Representation and Description:

Regional and boundary descriptors, boundary following, chain codes, perimeter polygons, description principal and components, signatures, decision recognition, structural methods, detection of discontinuities and relation descriptors.

Wavelet based Image Processing:

Wavelet transform in one and two dimensions, fast wavelet transform and wavelet packets.

Image Enhancement:

Spatial and grey level resolutions, zooming and shrinking, image enhancement basics, histogram equalization, histogram specification, logic and arithmetic operations enhancement, first and second order derivatives for enhancement and laplacian in frequency domain.

Object Recognition:

Patterns and pattern classes, template and shape matching, optimum statistical classifiers, syntactic recognition of string and trees.

Course Currilcum

                • Diploma in Digital Image Processing (Online Certification Courses) 02:00:00
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