Transforms for Digital Image Processing

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Functional representation of an image is f(x, y), where x and y are coordinates and amplitude f at any point gives the intensity of an image. Image processing is the conversion of image into image concerned variables using image processing techniques. There are three types of image processing techniques; they are digital, optical and analogue. Digital image processing techniques are most commonly used. It is really digital manipulation of images by considering various elements. These elements are called picture elements, image element, pels and pixels. Pixel is the term used most widely to denote the elements of a digital image. (Gonzalez, and Woods, 2). Pixel is the sample unit of an image which is represented by dots and squares. In colour system each pixel is represented as RGB parameters.

Fundamental steps in digital image processing

The fundamental steps in digital image processing involves many stages; image acquisition, enhancement, restoration, colour image processing, wavelets, compression, morphological processing. (Fundamental Steps in Digital Image Processing).

Image processing is done on the basis of Fourier transform. The Fourier transform is a generalization of the complex Fourier series in the limit as L ’. Replace the discrete An with the continuous F (k) d k, while letting n/L ’ k. Then change the sum to an integral, and the equations become. 

f (x) = Formula

(Fourier Transform).

  • Image acquisition: This is the starting stage of image processing, and usually involves the scaling.
  • Image enhancement : This process is used to improve quality of the image.
  • Image restoration: Images might have distortion, this technique is used to heal this.
  • Colour image processing: In this phase, distortion in RGB colour parameter can be reduced.
  • Wavelets: In this phase, images are divided into units of pixels. By using this, compression becomes easier.
  • Compression : The compression involves reducing the size of image.
  • Morphological processing : The objects in the image cannot be directly put into the image processing. So the easy way is to convert it into a binary image by using morphological processing. Making binary means, representation of each pixel as 0 or 1.

The basic concepts of the processes and issues associated with the acquisition of digital images

Processes behind the acquisition of digital images to convert into digital images are sampling and quantization technique. The image that is given in the question, first one is a continuous image, and that should be converted into digital format. It has two co-ordinates, that coordinate value will digitalize and this process is called sampling. Next step is digitalizing the amplitude, which is called quantization. After both processes, we get the second image. After continuous sampling and quantization we get the digital image.

Histogram equalization method

Histogram is the method of a graphical representation of an image or data by charting the frequency. Here, image is mentioned. It is acquired by the image processing tool box in mat lab. In the diagram, the bands are called categories and it is adjacent and non-overlapping. All bands have same size. It gives details of the concentration of the image. It can be drawn in two ways i.e. using histogram equalization method and by using image processing tool in mat lab. The histogram equalization method is the distinct alteration by means of image histogram. If we compare both histogram equalization and image tool box in mat lab, several steps are different from them, and image quality is also entirely dissimilar. Histogram equalization is as a contrast enhancement technique with the objective to obtain a new enhanced image with an uniform histogram. (Histogram Equalization).

It can be accomplished by grey scale mapping function. Because of distinct nature problem, the consequential histogram is not uniform as expected, although the cumulative appropriate histogram which looks like a direct line.

Conclusion

The digital image processing technique is most useful branch of a digital signal processing. The importance of the digital images techniques is explained above. The various steps of digital images are also mentioned. By using the technique, we can easily convert images into digital form.

Works Cited

Fourier Transform. Wolfram Math World: the Webs Most Extensive Mathematics Resources. 2009.

Fundamental Steps in Digital Image Processing. University of BATH: Transforms for Digital Image Processing. 2009. Web.

Gonzalez, Rafael C., and Woods, Eugene Richard. Digital Image Process. 3rd edition. Prentice Hall. 2007.

Histogram Equalization: Lesson. 1997. Web.

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