IMAGE PROCESSING: AN OVERVIEW
ANJALI TIWARI
COMPUTER SCIENCE, RAJ KUMAR GOEL INSTITUE OF TECHNOLOGY FOR WOMEN, INDIA
1033310007@RKGITW.EDU.IN
ABSTRACT
Image processing is a method in which we can process an image either by reducing distortion (noise effects) or by adding
image enhancing features or by storing it to a reduced size. We take an image as input such as a photograph from a mobile
phone or by using scanner which is connected to a computer and after processing it the output we get is either an image or is
represented in the form of real coordinates(x and y coordinated) i.e. the image produced is in the form of two-dimensional.
Users can process such images using either a command line language known as MATLAB
This paper deals with the improvement of the pictorial representation of an image by maximum clarity
I. INTRODUCTION
To process an image, the image needs to be in a digitized form. Once the image is digitized, the image processing operations must
be applied without reducing the characteristics of an image.
The first section describes what image processing is and the second section tells us about the operations used for the image
processing.
A. IMAGE PROCESSING
It is also known as digital image processing, in this the image required to be processed is a digital image on which signal processing
techniques can be applied.
Image processing refers to processing of a 2 dimensional picture by a computer. 2D pictures are represented in the form of matrices
having x and y coordinates.
Image processing helps to understand the nature of an image by:
 Improving its pictorial representation and information
 It is more easily understood by other machine
1.
Digital image:
Image processing refers to processing of a 2 dimensional picture by a computer. 2D pictures are represented in the form of matrices
having x and y coordinates. It is a discrete function.
F(x, y) =
2.
f11
f21
f12
f22
f1n
f2n
fn1
fn2
fnn
Digitization:
An image is digitized to convert it to a form which can be stored in a computer's memory or on some form of storage media such as
a hard disk .Digitization procedure can be done by a video camera mobile phone connected to a computer. After the image has been
digitized, it can be operated upon by various image processing operations.
B. IMAGE PROCESSING TECHNIQUES
Image Processing operations are applied to make the display and analysis of an image more useful. The operations are:
 Image Compression
 Image Enhancement and Restoration
 Information Extraction
These operations lead to maximum clarity and reduced size of the image.
1.
Image Compression:
It refers to compressing the size of an image without reducing its quality. As a result of this the image uses less storage space since
the number of bits gets reduced which is used to represent an image.
Compression can be done on various types of images:
 Text compression – CCITT GROUP3 & GROUP4
 Still image compression – JPEG
 Video image compression – MPEG
2.
Image Enhancement and Restoration:
Image restoration and enhancement helps in achieving the maximum clarity as well as the image quality. Features such as contrast,
boundaries or brightness can be sharpen to make the image more valuable or useful and restoration deals with the retrieval of the
degraded image back by reducing the noise, filtering, blurring and so on.
Image Restoration is concerned with filtering the observed image to minimize the effect of noise. Image restoration depends on the
extent and accuracy of the knowledge of degradation process as well as on filter design.
Enhancing can be done in various ways:
 By changing its brightness and its contrast, and this can be done is by w0rking with the image's histogram.
 By stretching the colour distribution
 By equalizing the distribution of colours to use the full range
 By adjusting the scaling of the colours
Some of the Enhancement techniques are:
Histogram: It is used to show the current level of contrast.Figure1 shows the histogram generation on mat lab software of an
original image and a binary image
Fig. 1
Image addition: It can be done by adding two images together. Figure 2 shows the addition of image 1 and 2 called as added
image and it also shows an image whose brightness is increased by adding 50.
Fig. 2
Enhancing and restoring is done to reduce the effects produced while acquisition and digitization. The content of the data do not get
increased it remains the same.
3.
Information Extraction:
Information extraction is also referred as pattern recognition. The aim is to extract information of the objects which is necessary to
recognize pattern. It can be done either by edge detection, segmentation and other techniques also.
Segmentation: It is a process in which an image gives us the meaningful segments. Image can be segmented using various types of
representation. It is also a first step in image analysis or pattern recognition.
Segmentation is based on one of two properties in an image:
(i) Similarity
(ii) discontinuity
Similarity is used to segment an image into regions which have grey levels within a predetermined range.
Discontinuity segments the image into regions of discontinuity where there is a more or less abrupt change in the values of the grey
levels.
It usually involves thresholding, which is done by setting the values of pixels above a certain threshold value to white, and all the
others to black. Because the objects touch, thresholding at a level which includes the full surface of all the objects does not show
separate objects. This problem is solved by performing a watershed separation on the image. Segmented image is shown in figure 3
Fig. 3
Edge Detection: This is used to detect the boundaries or edges in the image.
Edge detection is a method of segmenting an image into regions of discontinuity. In other words, it allows us to observe those
features of an image where there is a more or less change in grey level or texture
Edge detection is sensitive to noise. A black and white is converted into edged image shown in figure 4.
Fig. 4
II. CONCLUSION

Image stream contain extremely valuable data, whose contents is also very rich and diverse. The combination of audio and
image techniques, will definitely generate interesting results, and very likely improve the quality of the present analysis

Although a lot has already been revealed about the mind boggling OS, one can only guess what comes next.

Mat lab does have security issues but they may be overshadowed by the next versions to follow. Overall, Mat lab is a life
changing concept that is not limited only to the field of image processing. This is a revolutionary OS that could change the
way people think, and work.

Rest all depends on the near future.
ACKNOWLEDGEMENT
This paper would not have taken shape, without the guidance provided by Ms. Charu Gupta, who helped in our project and
resolved all the technical as well as other problems related to the paper and, for always providing us with a helping hand
whenever we faced any bottlenecks, inspite of being quite busy with their hectic schedules. Above all we wish to express our
heartfelt gratitude to HOD Ms. Kadambari Agarwal, whose support has greatly boosted our self-confidence and will go a long way
on helping us to reach further milestones and greater heights.
REFERENCE
[1] Computer Techniques in Image processing By Andrews 1970
[2] http://eleceng.dit.ie/papers/103.pdf
[3] Article in the January issue of journal, ELECTRONICS FOR YOU
[4] Digital image restoration By Andrews 1977
[5] Digital image processing By Rafael Gonzalez and Richard Woods 200
http://www.imageprocessingplace.com/downloads_V3/dip3e_downloads/dip3e_sample_book_material/dip3e_
[6] http://seminarprojects.com/Thread-digital-image-processing-full-report
[7] EE368/CS232: Digital Image Processing
http://www.stanford.edu/class/ee368/
[8]Fundamentals of Image Processing
ftp://qiftp.tudelft.nl/DIPimage/docs/FIP.pdf
chapter_ 01.pdf