Define the following with suitable examples
i) Unsharp marking
ii) High boost filtering
iii) High frequency filterin
Unsharp masking is a spatial domain image enhancement technique used to sharpen an image by emphasizing fine details and edges. The basic idea is to subtract a blurred (unsharp) version of the image from the original image to extract high-frequency components, and then add this detail back to the original. Mathematically, if the original image is denoted by f(x, y) and a blurred _____ ____ __________ ________ ____ ____.
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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).
In image restoration, how are the noise parameters estimated?
b) Assume that the noise is estimated as exponential, with mean Variance
. How will you estimate the parameter 'a' of pdf of exponential Noise?
) Propose a gray level slicing algorithm capable of producing the 4-bit plane of an 8-bit monochrome image.
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.
) Given an image f(x,y) with Fourier transform F(u,v) obtain the fourier transform of .
c) Given that the 2-D Fourier Tranform is real and even, obtain the constraints on the image characteristics.
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).
Apply the perception algorithm to the following pattern classes:,
.
Let and
Also, Sketch the decision surface.