Q19Digital Image Processing
Question
Explain the image restoration process. What are the different types of noise models? Discuss spatial filters used for noise removal.
Answer
Image restoration and noise models.
Image restoration aims to recover a degraded image using a priori knowledge of the degradation phenomenon. Common noise models include Gaussian, Rayleigh, Erlang, Exponential, Uniform, and Impulse (Salt-and-Pepper) noise. Each noise type affects the image histogram differently and requires specific filters for removal.
Spatial filters for noise removal include Mean filters (Arithmetic, Geometric, Harmonic) and Order-Statistics filters (Median, Max/Min, Midpoint). For instance, the geometric mean filter achieves smoothing comparable to the arithmetic mean filter but tends to lose less image detail, while the median filter is highly effective at removing impulse noise without blurring edges.