12-01-2013, 04:50 PM
Image Enhancement In Spatial Domain & Frequency domain
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ABSTRACT
Image quality and utility become crucial issues for engineers, scientist, doctors, patients, insurance companies and lawyer whenever there are changes in the technology by which medical images are achieved. Examples of such changes include analog to digital conversion, lossy compression for transmission and storage, image enhancement, and computer aided methodology for diagnosis of disease in medical images. Edit an image so that it is more suitable for a specific application than the original image is termed as image enhancement technique. Image is defined as a two dimensional function f(x, y), where x and y are spatial coordinates, that bears information, which can be generated in any form such as visual, x-ray and so on. X-rays are the oldest source of electromagnetic radiation used for medical imaging. Medical image enhancement methods are used like all other methods and algorithm in image processing, as chain subsequent edits aimed at achieving a suitable result. Improving one function in the chain is only useful if the end result is really unproved, and that does not solely depend on that particular function; it also depends on the quality of the first image. In this paper we have compared different types of image enhancement technique of medical image in spatial domain and also presented a statistical analysis.
Introduction Image enhancement is basically improving the interpretability or perception of information in images for human viewers and providing `better' input for other automated image processing techniques. The principal objective of image enhancement is to modify attributes of an image to make it more suitable for a given task and a specific observer. During this process, one or more attributes of the image are modified. The choice of attributes and the way they are modified are specific to a given task. Moreover, observer-specific factors, such as the human visual system and the observer's experience, will introduce a great deal of subjectivity into the choice of image enhancement methods. There exist many techniques that can enhance a digital image without spoiling it.
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 [1], we directly deal with the image pixels. The pixel values are manipulated to achieve desired enhancement. There are several enhancements in spatial domain such as
i. Gray Scale manipulation.
ii. Histogram equalization.
iii. Image smoothing-Neighborhood
averaging and Edge preserving smoothing. The term spatial domain refers to the aggregate of pixels composing an image.