Image Processing is processing of the image so as to reveal the inner details of the image for further investigation. With the advent of digital computers, Digital Image Processing has started revolutionizing the world with its diverse applications. The field of Image Processing continues, as it has since the early 1970’s, on a path of dynamic growth in terms of popular and scientific interest and number of commercial applications. Considering the advances in the last 30 years resulting in routine application of image processing to problems in medicine, entertainment, law enforcement, and many others. The discipline of Digital Image Processing covers a vast area of scientific and engineering knowledge. Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers. It’s built on a foundation of one- and two-dimensional signal processing theory and overlaps with such disciplines as Artificial Intelligence (Scene understanding), information theory (image coding), statistical pattern recognition (image classification), communication theory (image coding and transmission), and microelectronics (image sensors, image processing hardware). Image processing has revolutionized in various fields. Examples include mapping internal organs in medicine using various scanning technologies (image reconstruction from projections), automatic fingerprint recognition (pattern recognition and image coding) and HDTV (video coding).
Steps in Image processing:
The main steps involved in any image processing applications are as follows; Image acquisition:
In order to process any image the image must be acquired so as to perform the necessary processing. Images are generated by the combination of an illumination source and the reflection or absorption of energy from that source by the elements of the scene being imaged. The illumination may originate from a source of electromagnetic energy such as radar, infrared, or X-Ray image. Depending on the nature of the source the illumination energy is either reflected or transmitted through the object of interest. Special sensors are available for scanning the images.
Image compression solves the problem of reducing the amount of data required to represent the image. The basis of compression lies in removal of redundant data that might be useful for the purpose of storage. Image compression also plays a main role in transmitting data through Internet. Image enhancement:
Enhancement as the name indicates is to enhance the image so as to bring the details of the parts of the image which are obscured due to some distortion in the image. The principal objective behind image enhancement is to process the image so that it results in an image which is more suitable for the particular application where that image is applied than the original image.
Enhancement of the image using Filters:
Segmentation of the image is to subdivide a image into its constituent regions or objects. Image segmentation algorithms generally are based on one of two basic properties of intensity values: discontinuity and similarity. In the first category, approach is to partition the image based on abrupt changes in intensity, such as edges of the image. The second approach is to partition the image into regions that are similar according to set of predefined criteria. APPLICATIONS:
There are a wide variety of fields where Image Processing is applied. Some of them include
➢ analyzing geographical conditions
➢ weather analysis
➢ remote sensing .
Considering the importance of Image Processing in the field of Bio-Medicine the proposed system “OPTHALMIC ANALYSIS AND...
References: DIGITAL IMAGE PROCESSING BY - K R CASTLEMAN
FUNDAMENTALS OF DIGITAL IMAGE PROCESSING – AK JAIN, WWW.AMAZOM.COM
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