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Now a days digital
images have enveloped the complete world. The digital cameras which
are main source of digital images are widely available in the market
in cheap ranges. Sometimes the image taken from a digital camera is
not of quality and it required some enhancement. There exist many
techniques that can enhance a digital image without spoiling it.
First of all, let me tell you that the enhancement methods can
broadly be divided in to the following two categories:
1. Spatial Domain Methods
2. Frequency Domain Methods
In spatial domain techniques, we directly deal with the image
pixels. The pixel values are manipulated to achieve desired
enhancement. In frequency domain methods, the image is first
transferred in to frequency domain. It means that, the Fourier
Transform of the image is computed first. All the enhancement
operations are performed on the Fourier transform of the image and
then the Inverse Fourier transform is performed to get the resultant
image.
Before we proceed for the further discussion, I must tell you that
we will consider only gray level images. The same theory can be
extended for the color images too. A digital gray image can have
pixel values in the range of 0 to 255.
A Digital Gray Level Image
A digital gray image is a simple two dimensional matrix of numbers
ranging from 0 to 255. These numbers represents different shades of
gray. The number ‘0’ represents pure black color and number ‘255’
represents pure white color.
Create Negative of an Image
The most basic and simple operation in digital image processing is
to compute the negative of an image. The pixel gray values are
inverted to compute the negative of an image. For example, if an
image of size R x C, where R represents number of rows and C
represents number of columns, is represented by I(r,c). The negative
N(r,c) of image I(r,c) can be computed as
N(r,c) = 255 – I(r,c) where 0 <= r <= R and 0 <= c <= C
It can be seen that every pixel value from the original image is
subtracted from the 255. The resultant image becomes negative of the
original image.
Brightness Control
If the digital image is of poor brightness, the objects in the image
will not be visible clearly. It should be the case when the image is
captured under low light conditions. To rectify this problem, we can
further increase the brightness of the captured digital image and
make the image more attractive. If we study the histogram of a
low-brightness image, we will find that the most of the pixels lie
in the left half of the gray value range.
The brightness of a dark image can easily be increased by adding a
constant to gray value of every pixel. This addition operation will
shift the histogram towards brighter side with a constant factor.
While applying this method to increase brightness of an image, we
must choose the constant wisely so that the complete range of gray
values lies with in 0 to 255. If the final gray value of any pixel
is greater than 255 then we will loose the information. It will
create loss of information in the image.
Contrast Stretching
This operation is much better for the image quality enhancement in
comparison to brightness control. If low contrast image is resulted
due to low light conditions, lack of dynamic range of the camera
sensor, contrast stretching operation results in the good quality
image. During the contrast stretching operation, we basically
increase the dynamic range of the gray values. We can use different
functions for contrast stretching. The input range of gray levels
are mapped to a new range of gray levels using the transformation
function. We can use any non-linear function also for such mapping
of the gray levels.
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