Syllabus - Medical Image Processing (BM801)

Fundamentals of Image Processing and Image Perception

Two-dimensional systems - linear systems and shift invariance. Fourier transform - Z - transform - Block matrices, Toeplitz and Kronecker product. Luminance, brightness and contrast. Color representation, color matching and reproduction, color vision model. Image sampling and quantization. Two dimensional sampling theory, reconstructions of images from its samples. Image acquisition.

Image Enhancement Spatial Domain Techniques

Image negative, contrast stretching, gray level and bit plane slicing, power law transformation, histogram equalization and histogram specification, local enhancement techniques, image subtraction, averaging and logical operations. Spatial filtering: low pass, high pass and derivative filters, median filtering. Frequency domain filters: low pass, high pass and Butterworth filters.

Image Restoration

Noise degradation model, estimation of degradation model. Restoration in presence of noisespatial filtering, frequency domain filtering, inverse filter and least mean square error (Wiener) filtering.

Image Transforms

2D FFT and its properties. Walsh transform, Hadamard transform, discrete cosine transform, Haar transform, Slant transform, K L transform.

Image Analysis

Feature extraction, spatial features, amplitude and histogram features, transform features, edge detection: gradient, compass Laplace, Sobel, Prewitt operators, stochastic gradients. Line and spot detection. Boundary extraction: connectivity and contour following.