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?
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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?
Explain the functioning of an adaptive, local noise reduction filter.
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
Perform histogram equalization for the following histogram.
| Gray level | 0 | 1/7 | 2/7 | 3/7 | 4/7 | 5/7 | 6/7 | 7/7 |
| Number of occurrences | 400 | 700 | 800 | 900 | 500 | 400 | 196 | 200 |
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.
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).