Page 25 - Enhancing CAD Drawings with Photoshop

4386.book Page 8 Monday, November 15, 2004 3:27 PM

8 CHAPTER 1 THE BASICS

2. Zoom out to 25%. To do this, choose the Zoom tool in the toolbox or type Z on the keyboard.
Hold down the Alt key on the keyboard and click the center of the image until you reach a
magnification of 25%. This sizes the image in the Linework2.psd window down to a similar
size as the Linework.psd window.
3. With the Linework2.psd window selected, choose Image Image Size. There are 2000×1500
pixels in this image.
4. In the Image Size dialog box, uncheck Resample Image.

TIP Only use Resample Image when you want to change the number of pixels in the image.
5. Change the height to 6.25 inches. The width and resolution are automatically calculated from
this number. The resolution is 240 pixels/inch. Click OK to close the dialog box.
6. Select the Linework.psd window, and choose Image Image Size. This image has exactly
the same document size, but its resolution is only 72 pixels/inch. Therefore, the pixels in
Linework.psd appear more than three times bigger than the pixels in Linework2.psd.
Notice how the lines in Linework2.psd appear thinner and less jagged than the lines in
Linework.psd. You perceive the lines to be smoother when the pixels are smaller. The lines on
the left side of Linework2.psd (shown earlier in Figure 1.8) appear smooth, even though they
are aliased, because of the higher resolution.
7. Close both Linework.psd and Linework2.psd.

Raster Data Storage and Compression
Raster data is the color of pixels stored on a hard drive. Each pixel is given a color number, and these
numbers are stored in a matrix of columns and rows, called a raster.
The amount of raster data stored can be large for high-resolution images. When you store more
pixels, you need more disk space and memory. Data compression schemes are often used to cope with
the demands placed on storage and memory systems. Compression algorithms look for patterns in the
data (recognized by repetition or similarity) and can more efficiently represent patterns in a file as
compared with the raw, uncompressed data. Furthermore, compression schemes fall into two cate-
gories: lossless and lossy. Lossless compression preserves 100% of the original data, whereas lossy
compression is a trade-off between much smaller file sizes and degraded data.
Consequently, many file formats have arisen over time that deal with the compression issue in dif-
ferent ways. For example, the Windows bitmap (.bmp) format is uncompressed and therefore takes
a large amount of memory and disk space. An example of lossless compression is the Lemple-Zif-
Welch (LZW) method used in the Tagged Image File Format (.tif). The Joint Photographic Experts
Group (.jpg) format is lossy; it was designed to greatly reduce the size of photographic images, but
the trade-off is reduced quality. You will learn how to prepare and optimize compressed images for the
Web in Chapter 9, “Showing Your Clients.”

Understanding Modes, Bits, and Channels
To understand how images are stored on a computer, we will take a mental journey from the simplest
beginnings toward greater complexity. This journey will give you a solid foundation for working
with digital images in the future.