DSP in digital image processing



Digital signal processing (DSP) has been a growing and dynamic field for more than a decade. Therefore, nowadays, DSP has found applications in almost industry such as speed processing and seismic data processing have utilized the techniques of digital signal processing from the very beginning and in fact have been catalysts for many of the developments in the field. Others, such as audio processing, have in the past relied principally on analog signal processing methods and only recently have begun to exploit digital signal processing techniques. The purpose of this research is to give a background of one of the applications in digital image processing and then explain why DSP is an approximate solution. Some advantages and disadvantages are also given to show the potential of applying DSP for many techniques in the real world.


Digital image processing refers to a part of digital signal processing in which the signal is an image. It is the use of computer algorithms to perform image processing on digital images. Digital Image Processing is concerned with acquiring and processing of an image. In simple words an image is a representation of a real scene, either in black and white or in color, and either in print form or in a digital form i.e., technically a image is a two-dimensional light intensity function. In other words it is a data intensity values arranged in a two-dimensional form like an array, the required property of an image can be extracted from processing an image.With digital image processing, a much wider range of algorithms is applied to the input data, and the problems such as the build up of the noise and signal distortion which often happen in analogue image processing can be avoided in digital signal processing.


On the early 1920s, one of the first applications of digital images was in the newspaper industry, when pictures were first sent by submarine cable between London and New York. Specialized printing equipment coded pictures for cable transmission and then reconstructed them at the receiving end.

In mid to late 1920s, there is an improvement to the Bartlane system resulted in higher quality images.

Digital image processing really began to develop in 1960s. The first computers powerful enough to carry out meaningful image processing tasks appeared in the early 1960s. The birth of what we call digital image processing today can be traced to the availability of those machines and the onset of the space program during that period.

In the early 1970s digital image processing is used in medical imaging, remote Earth resources observations and astronomy.

From the 1970s until the present, the field of image processing has grown vigorously. In addition to applications in medicine and the space program, digital image processing techniques now are used in a broad range of applications.

In the 2000s, with the development of the computers with the fast processors, digital image processing has become the most popular method in image processing.


Digital Image Processing techniques are used to enhance, improve or otherwise alter an image and to prepare it for image analysis. The intention is to remove faults, trivial information or improve image.

The classifications of digital image enhancement algorithms in common use are point transforms and neighborhood operations.

3.1 Point transforms

Point transforms produce output images where each pixel is some function of a corresponding input pixel. The function is the same for every pixel, and is often derived from global statistics of the image. In other word, one image point is transformed into a new image point in a way that is not dependent upon its neighbors.

3.2 Neighborhood operation

With neighborhood operations, each output pixel is a function of a set of corresponding input pixel. This set is called a neighborhood because it is usually some region surrounding a corresponding centre pixel.

Linear filters are the best understood of the neighborhood operations, due to the extensively develop mathematical framework of signal theory. Linear filters can be defined by a convolution operation, where output pixels are obtained by multiplying each neighborhood pixel by a corresponding element of a link shaped set of values called a kernel, and then summing those product.


Digital Image Processing is being implemented in Vision System in Robotics. Robots capture the real time images using cameras and process them to fulfill the desired action. Consider that the robot's task is to move an object from one point to another point. The hand of the robot and the object that is to be captured are observed by the cameras, which are fixed to the robot in position, this real time image is processed by Digital Image Processing techniques to get the actual distance between the hand and the object. The operation to be performed is controlled by the micro-controller, which is connected to the ports of the fingers of the robot's hand. Using the software programs the operations to perform are assigned keys from the keyboard. By pressing the relative key on the keyboard the hand moves appropriately.

In this case, the usage of sensors or cameras and Edge Detection technique are related to digital Image processing and Vision Systems. By this technique the complexity of using manual sensors is minimized to a great extent and thereby sophistication is increased. Therefore, Digital Image Processing is used in study of robotics.


There are many applications for Image Processing like surveillance, navigation, and robotics. Robotics is a very interesting field and promises future development so it is chosen as an example to explain the various aspects involved in Image Processing. By the analysis of advantages and disadvantages of robotics which is the main application of the digital image processing to show the reason why digital signal processing is decided to apply for the most techniques in engineering.

5.1 Advantages

  • Cost is one of the reasons why digital image processing has benefited so much by these technology advancements.
  • Easy to store and use, that is why computers use it
  • Digital data is designed and artificially created, so it is efficient.
  • Vision Systems are flexible, inexpensive, powerful tools that can be used with ease.
  • In space exploration the robots play vital role which in turn use the image processing techniques.

5.1 Disadvantage

  • Digital communications require greater bandwidth than analogue to transmit the same information.
  • People need knowledge in many fields to develop an application or part of an application using image processing.
  • Calculations and computations are difficult and complicated so needs an expert in the field related. Hence it's unsuitable and unbeneficial to ordinary programmers with mediocre knowledge.


Digital image processing has many advantages over analog image processing, it allows a much wider range of algorithms to be applied to the input data

Digital Image Processing can avoid problems such as the build-up of noise and signal distortion during processing.

Digital image processing allows the use of much more complex algorithms for image processing, and hence can offer both more sophisticated performance at simple tasks, and the implementation of methods which would be impossible by analog means.

With digital image processing application, users are comfortable with many functions over analog image processing.

Moreover, digital image processing is also the cheapest method when comparing with other image processing.


It's a critical study, which plays a vital role in modern world as it is involved with advanced use of science and technology. The advances in technology have created tremendous opportunities for Vision System and Image Processing. There is no doubt that the trend will continue into the future. From the above discussion we can conclude that this field has relatively more advantages than disadvantages and hence is very useful in varied branches.


[1] WIKIPEDIA . 2008. Digital image processing. http://en.wikipedia.org/wiki/Digital_image_processing [11th December 2008].

[2]Rafael C. Gonzalez & Richard E. Woods, "Digital Image Processing", 2nd Edition, Prentice-Hall, Inc, 2002.

[3]Bill Silver, Chief Technology Officer, "An introduction to Digital Image Processing",

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