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Title: DNA COMPUTING

Description: DNA COMPUTING

A Few decades ago, image processing was done largely in the analog domain, chiefly by optical Devices. These optical methods are still essential to applications such as holography because they are Inherently parallel, however due to the significant increase in computer speed, these techniques are Increasingly being replaced by digital image processing methods. Digital image processing has a become a vast domain for modern signal technologies. Hence its applications pass for simple aesthetical considerations and they include medical imagery ,television and multimedia signals. It allows one to enhance image features of interest while attenuating detail irrelevant to a given application. And then extract useful information about the scene from the enhanced image. Digital image processing is a subset of the electronic domain wherein the image is converted to an array of small integers, called pixels, representing a physical quantity such as scene radiance, stored in a digital memory, and processed by computer or other digital hardware. Digital image processing, either as enhancement for human observers or performing autonomous analysis, offers advantages in cost, speed, and flexibility, and with the rapidly falling price and rising performance of personal computers it has become the dominant method in use. 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 or CD-ROM. This digitization procedure can be done by a scanner, or by a video camera connected to a frame grabber board in a computer. Once the image has been digitized, it can be operated upon by various images Processing operations. Image processing operations can be roughly divided into three major categories, Image Compression, Image Enhancement and Restoration, and Measurement extraction. Putting it all together often a complete digital image processing system combines many of the image Enhancement and analysis methods. In the broadest sense image processing is any form of information processing for which both input and output are images, such as photographs or frames of images. Most image processing techniques involve treating the images as a two dimensional signal and applying standard signal processing techniques to it. further details of image processing can be knowing about digital image processing. With the fast computers and signal processors available in the 2000s, digital image processing has become the Most common form of image processing , and is generally used because it is not only most versatile method, But also the cheapest. So digital image processing remains a challenging domain of programming.

Introduction:

Digital image processing is a broad field with extensive literature. This introduction could only summarize some of the more important methods in common use and may suffer from a bias towards industrial applications. 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. Introduction of the Bartlane cable picture transmission system in the early 1920s reduced the time required to transport a picture across the Atlantic from more than a week to less than three hours. Specialized printing equipment coded pictures for cable transmission and then reconstructed them at the receiving end. Some of the initial problems in improving the visual quality of these early digital pictures were related to the selection of printing procedures and the distribution of intensity levels.

The early Bartlane systems were capable of coding images in five distinct levels of gray. This capability was increased to 15 levels in 1929. Although the examples just cited involve digital images, they are not considered digital image processing results in the context of our definition because computers were not involved in their creation. Thus, the history of digital image processing is intimately tied to the development of the digital computer. In fact, digital images require so much storage and computational power that progress in the field of digital image processing has been dependent on the development of digital computers and of supporting technologies that include data storage, display, and transmission. However, the basis for what we call a modern digital computer dates back to only the 1940s with the introduction by John von Neumann of two key concepts:

(1)a memory to hold a stored program and data, and

(2) Conditional branching.

These two ideas are the foundation of a central processing unit (CPU), which is at the heart of The Computers today .starting with Von Neumann, there were a series of key advances that led to Computers powerful enough to be used for digital image processing. Concurrent with these advances Were developments in the areas of mass storage and display systems, both of which are fundamental Requirements for digital image processing. Like transistor. Cobal, ICs, OS, microprocessor, IBM, and, VLS In parallel with space applications, digital image processing techniques began in the late 1960s and early 1970 to be used in medical imaging, remote Earth re- sources observations, and astronomy. From the 1960s 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 archeology, image processing methods have successfully restored blurred pictures that were the only available records of rare artifacts lost or damaged after being photographed. In physics and related fields, computer techniques routinely enhance images of experiments in areas such as high-energy Plasmas and electron Microscopy. Similarly successful applications of image processing concepts can be Found in astronomy, Biology, nuclear medicine, law enforcement, defense, and industrial applications

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