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This lesson covers the basics of digital images, including encoding, standards, compression, and preservation. Students will learn about different color spaces, palette-based encoding, and the file size of images. They will also explore the question of whether a picture is worth 1000 words and the use of different number bases in computing.
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Communicating Quantitative Information Go over midterm Is a picture worth 1000 words? Digital images. Number bases Standards, Compression Will [your] images last? Homework: (Post project proposal). Work on Project.NEXT CLASS in computer classroom
Midterm • Will use results for lesson in frequency distributions and graphs (Excel) • Final will be similar • preparation guide • you can prepare a set of notes • cumulative
Digital images • Basic encoding • Is a picture worth 1000 words? • Standards • bmp, gif, jpg • Preservation issue • will the files last on storage medium • will there be appropriate software to display and manipulate the image
Basic encoding • Divide image into picture elements (pixels) • For each pixel (cell in the grid), record color • Different color spaces: • palette-based • RGB (redness, greenness, blueness) • YUV (Y=brightness, U and V together are hue and saturation) • other
Digital cameras marketing • More pixels (increased resolution) means that pictures can be 'blown up' more without showing pixelations • If you are NOT planning to make poster size pictures, you don't need more than 3megalpel? 5 megalpel? • cameras now competing on features like modes
Palette based • Think of painter's palette • Can only use those colors • If no match: • painter mixes up something (creates a new color on palette) • computer software dithers • produces spots of different colors that, hopefully, our eyes mix together to see desired color.
The software constructs palettewhen saving this image using a format with limited palette
Image file • Simple bit mapped, palette • (may include the palette, with general representation of the colors) • string of numbers, one for each pixel, indicating how that pixel is to be painted
Contrast • Painter (in smock) starts with palette • Computer software (PhotoShop, Paint Shop Pro, etc. doing conversions) can construct the best palette for a given photo
Encoding • Image file is all numbers!! • Actually, all bits (sequences of 1s and 0s) • Suppose, palette is black and white • 0 could stand for white • 1 could stand for black • Suppose, palette holds 4 colors • 00, 01, 10, 11 represent 4 distinct colors • Suppose, palette holds 256 colors • 00000000, 00000001, …. 11111111 There are 256 distinct patterns of 8 1s and 0s.
Quick exercise • How many different patterns can be made using 0s and 1s, 3 bits long? Make a list 000
General formula • Space N bits can hold 2N distinct patterns • 1 bit can hold 2 distinct patterns (represent 2 colors) 21 • 2 bits can hold 4 distinct patterns (represent 4 colors) 22 • 3 bits can hold 8 distinct patterns 23 • 8 bits can hold 28
Image [file] size • Say image is 300 by 400 pixels (300 wide, 400 high) • Each pixel is 8 bits (so the picture can have 256 colors—not especially big) • Say there is no compression (will get to this later) • Size is 300 * 400 * 8 bits • 960000 bits
1000 words • (Plain text file, not Word document) • How big is a word? Assume it averages out to 6 letters. • How many bits does a letter require? • In the standard encoding, 8 bits. • 1000 words occupies 1000* 6 * 8 = 48000 bits
Is a picture worth 1000 words? • Answer: it better because it costs/takes considerably more space. • compression reduces image sizes, but only so much
Digital camera • Uses a (large) palette • Records a number for what will be each pixel • There may be settings for color depth (amount of bits ~ numbers of colors) and resolution (size of pixel)
Standards (briefly) • gif: uses common strings, so repeated patterns do get compressed • compression is lossless. Can restore full detail. • restricted to 256 colors • Good for line art • jpg: uses common areas, but in a different color space and a different way (approximates changes in 8 by 8 blocks). For example, detects common levels of brightness. • compression is lossy. Cannot restore full detail. • can hold millions of colors: 8 bits for each of YUV. • Good for photographs
Number bases • Refresher: we use the decimal system: base 10 • 10 distinct symbols: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 • Base system • first column on the left is the ones/unit place (100) • second column starting from the left is the 10s place (101) • third column is the 100th place (102) • and so on…
Base 2 • Binary number system • have 2 symbols: 0 and 1. These are called bits! • Base system • first column on the left is the ones/unit place (20) • second column is the 2-place (21) • third column is the 4-place (22) • and so on • Fewer symbols (simpler circuitry), longer strings of symbols needed
Warning • bit is either a 0 or a 1. Abbreviation b • byte is 8 bits. Abbreviation B • k may mean 1000 or 1024 (a power of 2) • Mega-bit, Mega-byte, Mega-pel 1000000 bits, bytes or pixels… • Gigabyte: 1000000000
Base 16 • Hexadecimal • 16 symbols: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E, F. • first column is the 1s place • second column is the 16th place • third column is the 256th place • and so on.
Exercise • Write your age in • decimal • binary • hexadecimal • How many 16s are there (probably just 1)? • What is left over?
Use of Hexadecimal • RGB colors • Each of red, green, blue is allocated 8 bits takes up 2 hexadecimal digits (bad term) • Deep red is FF0000 • Deep blue is 0000FF • white is FFFFFF • black is 000000
Will digital images last Depends on • storage medium. Hard disks can fail. CDs and DVDs can get damaged. Memory sticks fairly robust, but ends can get damaged (and they can get lost) • software: Need software that 'knows' the standard used for the picture • Software for display, manipulation, printing
Linear Perspective • Perspective:a technique for representing three-dimensional space on a flat surface.
Linear perspective • is based on the way the human eye sees the world:objects which are closer appear larger, and more distant objects appear smaller. • Objects are drawn using orthogonal lines which lead to the vanishing point(s).
Linear perspective • In one-point perspective, the forms are seen face on and are drawn to a single vanishing point. • Objects seen at an angle would be drawn with two-point perspective using two vanishing points.
Other perspectives • Cameras can supply other perspectives, depending on point of focus • Suitable topic for Project 2 • See next several charts for 2-point perspective • (I will skip to next topic).
