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COSC 109 (7)
Chapter 2

# COSC 109 Chapter 2 Notes.doc Premium

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School
Department
Computer Science
Course
COSC 109
Professor
Mona Tavakalon
Semester
Fall

Description
COSC 109 Chapter 2 Chapter 2: Fundamentals of Digital imaging Digitization is to convert analog information to digital data. • -Digitization is a 2-step process 1. Sampling 2. Quantization In order to get a picture from being blurry you can increase the sampling rate and the bit depth. Both of these cause the file size to increase. • Sampling rate refers to how frequent you take a sample. Ex. Increasing image size from 25 x 20 to 100 x 80 In digital imaging when you increase the sampling rate it is the same as increasing the image resolution. There are consequences of higher image resolution: • You have more pixels (sample points) to represent the same scene, meaning that the pixel dimension of the captured image is increased. Ex. Increasing image size from 25 x 20 to 100 x 80 • The file of the digitized image is larger • You gain more detail from the original picture In the real world a natural image has an infinite number of colors, its colored in continuous tones. But the discrete and finite language of the computer restricts the amount of colors and shades. Quantization is to encode a infinite number of colors and shades with a finite list • Quantizing an image involves mapping the color of each pixel to a discrete and precise value • First you will need to consider how many possible colors you want to use in the image Ex. If you want to map 4 colors you need 2 bits • When quantizing an image you reduce the number or allowed colors in the image • So when we reduce the colors, colors in the image may be mapped to the same color on the palette that doesn’t match but that is closest to original color. This reduces the details in the image. The more colors you use the clearer the image. The number of colors used for quantization is related to the color depth or bit depth of the digital image. • A bit depth of n allows 2 different colors 24 • The most common bit depth is 24. A 24-bit image allows 2 colors (16,777,216) In most cases increasing the number of colors in the palette improves the image fidelity. The number of colors or the bit depth is not the only determining factor for image fidelity in quantizing an image. The choice of colors for the quantization also plays an important role in the reproduction of an image. • The higher the bit depth the more bits to represent a color. Therefore an image with a higher bit depth has a larger file size than the same image with a lower bit depth. Bitmapped images are divided in a grid. Each cell in the grid stores only one color value. Each cell is called a pixel (picture element). Bitmap images are resolution dependent, meaning that each image has a fixed resolution. The level of details the image can represent depend on the number of pixels. Example of bitmapped images • Web images, JPEG, PNG, GIF • Adobe Photoshop images Bitmapped images saves pixels one by one. Each pixel is converted to a bit. Bitmap images are resolution dependent. The difference between bitmap and pixmap images is that bitmap refers to images with 1 bit per pixel and pixmap has a color value that uses more than 1 bit, Vector graphics you pick a start and end point and you choose whatever resolution you would like. Ex. Graphics created in adobe flash and adobe illustrator Vector graphics are resolution in
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