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Contrast Enhancement of an Image
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CONTRAST ENHANCEMENT
Contrast enhancement is done by scaling all the pixels of the image by a constant k.It is
given by
g[m,n]=f[m,n]*k
changing the contrast of an image , changes the range of luminance values present in the image.
Specifying a value above 1 will increase the contrast by making bright samples brighter and
dark samples darker, thus expanding on the range used. A value below 1 will do the opposite
and reduce a smaller range of sample values.
Algorithm Contrast Enhancement
Read the original image
Enter the contrast limits for input and output
Adjust the contrast levels using line equation
Display the contrast enhanced image
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low pass filter
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HISTOGRAM PLOTTING
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Aim:
To write a program for histogram plotting of the image.
Theory:
The histogram of an image is the plot of the number of occurrence of gray levels in the
image against the gray-level values. The histogram provides a convenient way of expressing the
intensities in an image, but it is unable to convey any information regarding spatial relationship
between pixels. The histogram provides more insight into about image contrast and brightness.
The histogram of a dark image will be clustered towards the low gray level values while that of
bright image will be clustered towards higher gray level. Similarly the histogram of a low
contrast image will not be spread equally and for high contrast image histogram will have an
equal spread in the gray level values.
The histogram of a digital image with gray levels in the range of [0,L-1]is a discrete
function h(r k ) = n k ,where r k is the kth gray level and n k i
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HISTOGRAM EQUALISATION OF AN IMAGE
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Objective: To investigate the mechanism of the disease
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2D CONVOLUTION
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Aim:
To write MATLAB function for 2-D convolution.
Theory:
2-D convolution can be performed through matrix multiplication. To do this, form ,the
block matrices H0,H1 etc. from one of the matrices and block toeplitz Matrix has to be formed
from the block matrices.The other matrix is written in column form. Then the multiplication
between the block toeplitz matrix and the matrix written in column form will yield a result
similar to 2D convolution.
Let the size of the matrix x [m,n] be M1X N1 ,where M1 is the number of rows and N1 be
the number of columns of the matrix x[m,n].
. Let the size of the matrix h [m,n] be M2X N2 ,where M2 is the number of rows and N2 be
the number of columns of the matrix h[m,n].
The convolution between x(m,n) and h(m,n) is denoted by y(m,n)
Where
y(m,n)= x(m,n) * h(m,n)
The size of the matrix y [m,n] is M3X N3 ,where M3 = M1 +M2 -1 and N3 = N1+ N2 -1
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