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Example research essay topic: Black And White Electrical Impulses - 2,017 words

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Overview Digital cameras capture images electronically and convert them into digital data that can be stored and manipulated by a computer. Like conventional cameras, digital cameras have a lens, aperture, and shutter, but they dont use film. When light passes through the lens it is focused on a photo-sensitive electronic chip called a charged coupling device (CCD). The CCD converts light impulses into electrical impulses (also called analog signal forms).

The signals are fed into a microprocessor and transformed into digital information. This process is called digitization. Although digital images do not yet match the quality of pictures produced on film, they represent an enormously flexible medium. Photographers are no longer limited by the physical properties of chemistry and optics.

Computers outfitted with the appropriate software can augment and transform images in ways never before imagined. History The origins of digital cameras are intimately linked with the evolution of television in the 1940 s and 50 s, and the development of computer imaging by NASA in the 1960 s. Before the advent of the video tape recorder (VTR), television images were optically displayed on monitors and then filmed by motion picture cameras. Because film and television technologies were essentially incompatible, Kinescopes, or " kinds" as they were called, produced inferior images. A breakthrough occurred in 1951 when Bing Crosby Laboratories introduced the VTR, a technology specifically designed to record television images.

Television cameras convert light waves into electronic impulses, and the VTR records these impulses onto magnetic tape. Perfected in 1956 by the Apex Corporation, video tape recording produced clear, crisp and nearly flawless images. The use of Vtr's soon revolutionized the television industry. The next great leap forward happened in the early 1960 s as NASA geared up for the Apollo Lunar Exploration Program.

As a precursor to landing humans on the moon, NASA sent out a series of probes to map the lunar surface. The Ranger missions relied on video cameras outfitted with transmitters that broadcast analog signals. These weak transmissions were plagued by interference from natural radio sources like the Sun. Conventional television receivers could not transform them into coherent images. Researchers at Nasa's Jet Propulsion Laboratory (JPL) developed ways to " clean" and enhance analog signals by processing them through computers.

Signals were analyzed by a computer and converted into numerical or digital information. In this way, unwanted interference could be removed, while critical data could be enhanced. By the time of the Ranger 7 mission, JPL was producing crystal clear images of the moons surface. The age of digital imaging had dawned. Since that time, probes outfitted with digital imagers have explored the boundaries of our solar system.

The orbiting Hubble telescope, a hybrid of optical and digital technology, maps the limits of the known universe. Here on earth, digital techniques gave rise to a host of medical imaging devices, from improved X-ray imaging in the late 1960 s, to Magnetic Resonance Imaging and Positron Emission Tomography in the 80 s and 90 s Thousand Points of Light: How Digital Images Are Formed Digital cameras come in several formats designed for the specialized needs of photographers. They range from inexpensive snapshot models to sophisticated scanner backs that fit on professional large format film cameras. Regardless of their size or sophistication, all digital cameras operate in much the same way.

All images we perceive are formed from optical light energy. Even digital images created within a computer are eventually converted into light energy that we can see. In order for a digital camera to store an optical image, it must be converted into digital information. A digital camera gathers light energy through a lens, and focuses it on a CCD which converts it into electrical impulses. These signals are fed into a microprocessor where they are sampled and transformed into digital information. This numerical data is then stored, and usually transferred later on to a computer where the image can be viewed and manipulated.

Black-and-White Basics A black-and-white photograph is composed of a wide range of tonal variations. Like the spectrum of natural light it represents, the photos tones are continuous and unbroken. By contrast, a black-and-white digital image consists of myriad points of light sampled from the light spectrum. A digital images range of tone is determined by the cameras capacity to sample and store different light values. After the CCD converts light into an electrical signal, it is sent to the image digitizer. The digitizer samples areas of light and shadow from across the image, breaking them into points pixels.

The pixels are next quantized assigned digital brightness values. For black-and-white, this means placing the pixel on a numerical scale that ranges from pure white to pure black. In color imaging, the process includes scales for color resolution and chromatic intensity. Spatial Resolution: Each pixel is assigned an x, y coordinate that corresponds to its place and value in the optical image. The more pixels, the greater the images range of tone. This quality is called spatial density, and is a vital component of image quality.

How good a picture looks is also affected by optical resolution meaning the cameras optics and electronics. Together, spatial density and optical resolution determine the images spatial resolution; its tonal spectrum and clarity of detail. In the end, spatial resolution is decided by the cameras lesser most quality: spatial density or optical resolution. Spatial Frequency If crisp, clear pictures are the result of spatial density, then a cameras digitizer should sample an image as broadly and often as possible. The digitizers ability to do this results in the images spatial frequency. Imagine a picture of a palm tree on a sandy beach.

The sky is bright blue with barely a cloud in the sky. The sand is golden, and covered here and there by white breakers. The ocean is an unbroken expanse of deep blue. The palms dark forest greens are broken by shafts of filtered light.

When the digitizer scans this image it will find the sky, beach and ocean fairly simple patterns of continuous tones. They vary little in brightness or color; one sampled point of light is pretty much the same as the next one. These areas have low spatial frequency. The digitizer doesnt need many samples to accurately read their tones. The tree, however, with its deep shadows and brilliant highlights, presents a greater challenge. Bright tones and dark tones vary greatly from one pixel to the next.

This rapid rate of tonal shifting is called high spatial frequency. In order to build an accurate representation, the digitizer needs many more samples than it does for a low frequency area. After determining the area of highest spatial frequency, the digitizer calculates a sampling rate for the entire image. That speed is double the rate of the images highest spatial frequency. In this way the digitizer captures all of the scenes subtle tonal nuance. Of course, the cameras sampling rate is not infinite, especially in lower priced models.

Its ability to sample is limited by its number of pixels. Pixel density depends on the amount of capacitors on the CCD chip. This varies quite a bit between different makes and models of cameras. Generally, cameras are assigned spatial frequency rates that cover most situations photographers are likely to encounter. Brightness Resolution The apparent brightness of an object in the real world is quite different from its representation in a picture. Anyone who has ever gazed at the sun instinctively knows the difference between the actual object and a photograph of it.

This may seem an academic distinction, but it is a key concept in digital imaging. The sun, the moon, the trees and flowers everything we see in our physical environment possess radiant intensity. They emit and reflect light energy. Paintings, photographs, and digital images, on the other hand, possess luminous brightness. Though they have radiant intensity, it is not the same intensity as the objects they represent. The sun shown on a television or movie screen does not have the radiant intensity of the actual celestial body.

It is a representation. In a digital photograph, each pixel has an assigned brightness value luminous brightness that corresponds to a radiant intensity in the physical world. This value is determined by how many bits are in the quantized. A 3 -bit quantized, for example, can only render a scale of eight distinct tones ranging from pure white to pure black. If this camera took a picture of our beach scene, it would create a high contrast image with very few middle tones. This effect is called brightness contouring, and is similar to the phenomenon of poster ization in conventional photography.

Brightness contouring has many pragmatic and creative applications when an image is ready to be manipulated in a computer. However, when capturing images with a camera, its best to preserve as wide a tonal range as possible. Every bit added to a quantized doubles its scale of tones. Most modern digital cameras are equipped with 8 -bit quantizer's capable of producing 256 different shades.

Some professional quality cameras have quantizer's that can render well over a thousand tones. Color Resolution Making digital images in color requires an additional step. In black-and-white, the brightness resolution of a pixel is determined by one gray value. In color, that value has three components, one for each primary color, red, green or blue. This concept is called trichromat. Color digital cameras are outfitted with three different sensors, each one sensitive to a primary waveband of light.

After an image is scanned and quantized, it is further broken down into color values. Each pixel is assigned three color values which represent qualities of red, green or blue. Color values are further distinguished by their hue saturation and brightness. Suppose, for example, a photographer snaps an image of a pink balloon. The cameras red sensor is stimulated and the quantized assigns the pixels that hue.

Next, a saturation value is determined. Deep red is a fully saturated color, while pink is much less saturated. It is relatively faded and much closer to the white extreme of the scale. Lastly, the brightness value determines the luminous intensity of the color.

Is this a pink balloon drifting through the shade of a forest? Or does it float freely across a bright blue sky? These considerations will compose the saturation and intensity of the image. Digital Imaging: From Camera to Computer Most digital images form within a blink of the cameras shutter. In that fragmentary instant, an image made of light is transformed into a stream of numerical data by a complex web of technologies.

Whats more, the image stored within the cameras memory chip is only the beginning. To be viewed and appreciated, the cameras data must be uploaded into a computer. Here, an imaginative photographer can alter and transform the image in almost any way desired. With the proper software, even the most mundane snapshot can evolve into a work of artistry. The political, social and artistic ramifications of digital imaging technology are yet to be ascertained. One thing is certain: the way we create and perceive the fruits of human imagination will never be the same.

Bibliography Books Based, Gregory, Digital Image Processing: Principles & Applications, New York: John Wiley & Sons, Inc. , 1994. Brown, Les, Les Browns Encyclopedia of Television: Third Edition, Detroit: Gale Research, 1992. Grotta, Sally Wiener, and Grotta, Daniel, Digital Imaging for Visual Artists, New York: Wind crest/McGraw-Hill, 1994. Katz, Ephraim, The Film Encyclopedia: Second Edition, New York: Harper Perennial, 1994. Articles Big, Edward C. , " Smile Youre on Candid Computer, " Business Week, 4 November 1996. Diehl, Stanford, " Bytes Video Workshop, " Byte, May 1995.

John, Alan, " Beyond Hollywood, " Byte, May 1995. Lu, Cary, " Digital Cameras on the Move, " MacWorld, June 1996. McNamara, Michael J. , " New Imaging, Today & Tomorrow: 3 New Digital Cameras, " Popular Photography, August 1996. Wiener, Leonard, " Camcorders Go Pro, " U. S. News & World Report, 25 November 1996.

Zuckerman, Jim, " Digital Portraits, " Petersen's Photographic, September 1996.


Free research essays on topics related to: digital imaging, digital cameras, black and white, electrical impulses, light energy

Research essay sample on Black And White Electrical Impulses

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