SPATIAL DOMAIN METHODS:
The term spatial domain refers to the aggregate of pixels composing an image, and spatial domain methods are procedure that operates directly in this pixel
Image processing function in the spatial domain may be expressed as
g(x,y) =T[f(x,y)]
Where f(x,y) is the input image and g(x,y) is the processed image, and T is an operator on f, defined over some neighborhood about(x,y)
FREQUENCY DOMAIN METHODS:
The foundation of frequency domain technique is the convolution theorem .Let g(,y) be an image formed by the convolution of an image f(x,y)and a linear position, position invariant operator h(x,y) that is, g(x,y) = h(x,y) * f(x,y)
Then from the convolution theorem, the following frequency domain relation holds:
G( u,v) = H (u , v)F(u , v)
Where G,F &H are the Fourier transforms of g,h &h respectively.
we compute the fourier transform of the image to be enhanced,multiply the result by a filter(rather then convolve in the spatial domain )and take the inverse transform to produce the enhanced image
ReplyDeleteI agree with you on the point that Image enhancement methods are many times needed.The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide `better' input for other automated image processing techniques.The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide `better' input for other automated image processing techniques.
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