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IMAGE PROCESSING

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.

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.

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

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.

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.

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