image noise definition
any entity in image that is not interesting for the purpose of the main computation
gaussian noise
additive noise , no correlation between pixels
impulsive noise
individual noisy pixels, intensity differs significantly from true intensity and neighborhood
mean filter
averaging in a local neighborhood of pixels
not good for salt and pepper noise
blures edges, cannot show periodic patterns
convolution
flipping of the filter at both axes
negative sings of the indices h(-i,-j)
main steps of convolution
flipping of the filter
multiplication of the vilter values with image intensity values
summation of the mutiplication results
gaussian filter
2D gaussian filter so transition from filtr mask values to surrounding zero values is not so abrupt
Discretization of gaussian filter
choose the standard deviation for the gaussian
choose the size N of filter mask
compute the discrete values of the filtr mask
non linear filters
median filter
pixels in NxN neigborhood are sorted and median value assigned to middle pixel
no bluring
edge detection steps
noise reduction
edge enhancement
edge detection
edge localization
image gradient
orthogona to the edge direction → direction of steepest slope of the intensity function
magnitude → maxiumum rat eof increase
image gradient for continuous and discrete functions
prewitt derivative operators
differende between the columns adjecent to the central column (same for rows)
difference between correlation and convolution mask
convolution incluedes flipping along x- and y-axes
sobel derivative operators
elements closest to the central point are weighted twice
edge detection with gradient operators stepwise
for each pixel
compute the image gradient
cmpute the gradient magnitude
compare magnitude to threshold
refine the edge postion by non-maximum suppression