Explain the functioning of an adaptive, local noise reduction filter.
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Show that Sobel masks can be implemented by one pass of differencing mask of the form [−1 0 1](or its vertical counterpart) followed by a smoothing mask of the form [1 2 1] (or its vertical counterpart).
Suppose a low-pass spatial filter is formed by averaging the four immediate neighbours of a point (x, y) but excluding the point itself. Find the equivalent filter H(u,v) in the frequency domain.
Filter the given gray level image with
i) mean filter using zero padding
ii) 3×3 weighted mean filter using zero padding with mask
iii) 3×3 median filter processing only such pixels that have all the needed neighbours.
iv) Laplacian filter with the given mask and reflecting the border pixels.
Describe the homographic filtering. Explain why the filtering scheme is effective for the applications it is used.
Explain the Hough transform for edge linking with suitable example.
Given that
where f and g are real images and h is a spatial filter.
Obtain G(u,v), in terms of F(u,v), and H(u,v), the 2–D Fourier transform of g(x,y).
Given an image with uniform histogram. Explain the effect of applying following compression techniques:
i) Huffman,
ii) Golomb,
iii) LZW,
iv) Prediction coding, and
v) Optimal Quantization