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Text and Images Key Revision Points.

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Presentation on theme: "Text and Images Key Revision Points."— Presentation transcript:

1 Text and Images Key Revision Points

2 Text - ASCII The problem:
Representing text strings, such as “Hello world”, in a computer Character set maps letters (or symbols) to numeric values which can be stored as binary numbers One common coding system/character set is ASCII 7-bit code - 8th bit is unused (or used for a parity bit) – still requires one byte of storage per character 2^7 = 128 codes = 128 unique characters can be represented in the basic ASCII character set

3 Text – Extended ASCII and Unicode
Extended ASCII uses all 8 bits – 2^ codes = 128 unique characters can be represented in the extended ASCII character set Still not enough e.g. no £ sign or “foreign” characters The Unicode character set uses 16 bits per character. Therefore, the Unicode character set can represent 216, or over 65 thousand characters

4 Text - Next In Sequence…
“What is the binary value of the next ASCII letter in the sequence. A= , B= , E=????” To get the answer: Convert to denary first E.g =65, =66… Work out next denary number(s) in sequence e.g. C=67, D=68, E=69 Convert to binary E.g. E= 69 =

5 Images Bitmap images are made up of individual pixels (picture elements). In memory or storage the colour of each pixel is represented as a binary number. The image is therefore stored as a series of binary numbers Colour depth or bit depth describes how many memory bits are used to store the colour of each pixel

6 Images – Bit Depth The more bits you use for storing data about each pixel the more unique colours an image can have: A 1 bit image can only have 2 colours An 8 bit image can have 256 colours A 24 bit image can have 16 million + colours!

7 Images – Bit Depth 1 bit – 2 unique colours 4 bit – 16 unique colours

8 Formula Max. number of unique colours = 2 to the power of bits
E.g. 4 bit image = 2 ^ 4 = 16 colours E.g. 8 bit image = 2 ^ 8 = 256 colours

9 Resolution Resolution is the number of pixels in an image.
Higher resolution  better quality images Lower resolution  pixilation Measured in PPI (pixels per inch) 40PPI means 1600 pixels in a one inch square 80PPI means 6400 pixels in a one inch square

10 File Size Without this info the image wont be displayed correctly
The higher the bit (colour) depth and resolution the bigger the file Theoretically we can calculate the size of an image file e.g. 1 inch 40PPI image using a bit depth of 4 40 x 40 pixels = 1600 pixels in total. Each pixel requires 4 bits so 4 x 1600 = 6400bits To convert to bytes divide by 8 (8 bits in a byte) bits = 800 bytes In reality the file will be bigger as it also needs to contain metadata – data about the image File format Height Width Colour depth Resolution Without this info the image wont be displayed correctly

11 Textbook Textbook pages 72-73


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