© 2016 AQA. Created by Teachit for AQA 3.3.5 Character encoding and 3.3.6 Representing images Lesson.

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Presentation transcript:

© 2016 AQA. Created by Teachit for AQA Character encoding and Representing images Lesson

© 2016 AQA. Created by Teachit for AQA Objectives – Character encoding Understand how ASCII and Unicode are used to represent a range of printable text and characters. Identify sequential patterns for the characters. Match ASCII values to their characters. Know how Unicode can be used for a wider range of characters.

© 2016 AQA. Created by Teachit for AQA Objectives – Representing images Define the word ‘pixel’. Explain how an image may be broken down using a grid to provide pixels with known coordinates. Explain how various colour schemes may be digitally encoded. Calculate the size of a digitally encoded image.

© 2016 AQA. Created by Teachit for AQA How characters are represented using ASCII Maximum possible binary value using ASCII = = = ‘N’ Minimum possible binary value using ASCII = 0 10 This is how the letter N would be represented. !"#$%&'()*+,./ :; ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_` abcdefghijklmnopqrstuvwxyz{|}~ This is the whole set of printable characters. Look at the sheet of all the ASCII characters.

© 2016 AQA. Created by Teachit for AQA ~ h G / What character is represented by this 7-bit ASCII character code?

© 2016 AQA. Created by Teachit for AQA How characters are represented using Unicode Unicode uses 16 bits to represent the character range. Using 16 bits gives 2 16 combinations or 65,536 possible binary patterns. Unicode values are usually shown using hexadecimal. Character Ç ɸ Шق ∯ Hexadecimal value 00C703D50428FED6222F Description (Latin) Capital letter C with cedilla (Greek) Phi Symbol (Cyrillic) Capital Letter Sha (Arabic) qāf Mathematical surface integral symbol The Unicode Standard covers (almost) all the characters, punctuations, and symbols in the world.

© 2016 AQA. Created by Teachit for AQA In order to represent images digitally, there are two areas that we need to look at: resolution – the size of each pixel in the image (i.e. how many there are) colour depth – how the colours of an image may be represented by digital encoding. Representing images

© 2016 AQA. Created by Teachit for AQA Pixel 0,0Pixel 0,7 Pixel 7,0Pixel 7,7 The original image Overlaying the image with a grid. Representing images – looking at resolution

© 2016 AQA. Created by Teachit for AQA Pixel 0,0Pixel 0,15 Pixel 15,0Pixel 15,15 Look what happens if we add a smaller square to the original. Overlaying the image with a 16 x 16 grid. Element smaller than grid square Increase scanning resolution Representing images – looking at resolution

© 2016 AQA. Created by Teachit for AQA We need to map the grid capture into a digital format The simplest way is to map each square as on (1) or off (0). Each row can then be stored sequentially in an image file. Pixel 0,0Pixel 0,7 Pixel 7,0Pixel 7,7 Row number Row Row Row Row Row Row Row Row Representing images – transforming the image to a bitmap

© 2016 AQA. Created by Teachit for AQA How big would the first 8 x 8 image be? We would need 64 bits to store the bitmap. How big would the second 16 x 16 image be? We would need 256 bits to store the bitmap. Why does the second image need 256 bits? Because the grid is 16 bits x 16 bits which makes 256b bits in total. Representing images – transforming the image to a bitmap

© 2016 AQA. Created by Teachit for AQA Representing images – looking at colour depth Pixel 0,3 is green Pixel 7,0 is whitePixel 7,4 is red The original image Overlaying the image with a grid

© 2016 AQA. Created by Teachit for AQA Cell locationRed intensityGreen intensityBlue intensity 7, , , Representing images – looking at colour depth

© 2016 AQA. Created by Teachit for AQA Image size in bits = W x H x D = 8 x 8 x 24 = 1536 bits Representing images – calculating bitmap file size