ACARA Digital Technologies Years 9–10 — Data Compression Hangman

The 38 key terms

1File size

How much storage a file needs, based on how much data (text, image, audio) it contains.

2KB, MB, GB, TB

Units of storage size built on the byte. Each unit is about 1000 times bigger than the one before: 1 KB, then 1 MB, then 1 GB, then 1 TB. Use them to check if files fit on a drive.

3character code

A number the computer uses to stand for one letter or symbol. It stores the number, then turns it back into the character on screen. In one A=1 code, A is 1 and B is 2.

4pixel

A pixel is one tiny square in a grid that makes up a digital image. Each pixel is stored as a number, such as 0 for white or 1 for black.

6resolution

The number of pixels in an image, given as width x height (like 1920 x 1080). More pixels give more detail but make a bigger file.

7colour depth

The number of bits used to store the colour of each pixel. More bits per pixel means more possible colours, such as 1 bit for 2 colours or 24 bits for true colour.

8Sampling

Measuring a sound wave thousands of times per second and storing each measurement as a binary number.

9sample rate

The number of sound measurements taken each second, in hertz (Hz). CDs use 44,100 Hz. A higher rate gives better quality but makes a bigger file.

10sample resolution

The number of bits used to store each sample of a sound. More bits give more possible volume levels and a more accurate recording. 16 bits per sample is common.

11Compression

Reducing file size by removing or simplifying data, sometimes losing quality.

12compression saves storage

Compressed files are smaller, so they take up less storage space. This means more photos or songs fit on a device, and less storage needs to be bought.

13compression saves bandwidth

A compressed file has fewer bits to send, so it uses less of the shared network bandwidth. This eases congestion and helps video and audio stream smoothly.

14transmission time

The time a file takes to upload, download or send. A smaller compressed file has a shorter transmission time, so downloads, email attachments and web pages are quicker.

15redundancy

Repeated or predictable data, like a run of the same letter or colour, that can be stored in a shorter form without losing any information.

16lossless compression

Shrinks a file so the exact original data can be rebuilt perfectly, with nothing lost. ZIP and PNG use it. Needed for text and programs.

17dictionary compression

Give each repeated word or phrase a short code, store the code table once, then replace every repeat with its code so the data takes up fewer characters.

18variable-length coding

Gives common characters short bit codes and rare ones longer codes, so a whole message uses fewer bits than if every character used the same fixed number of bits.

203C2D = CCCDD

Decoding run-length data: read each count then its character, and write that character that many times. 3C means CCC and 2D means DD, so 3C2D expands back to CCCDD.

21RLE pixel row

Run-length encoding of a pixel row stores each run of same-coloured pixels as a count then a colour code, in order along the row. E.g. WWWBB becomes 3W2B.

22run-length encoding

Compress a black-and-white image by writing each row as counts of same-coloured pixels in a run, starting with white. Row 00000 111 00 becomes 5,3,2. Counts can rebuild the grid.

23RLE decode

Repeat each colour code count times along the row to rebuild the pixels, e.g. 3R2B gives RRRBB. Then check the row adds up to the image width.

24RLE expansion

When data has few repeats, run-length encoding adds a count to every character, so the result can be longer than the original. It only saves space when the data has long runs.

25decompression

Reversing compression to turn a compressed file back into usable data. Only lossless decompression restores the exact original; lossy data that was removed is gone for good.

26lossy compression

Shrinks a file by permanently throwing away detail people are unlikely to notice, so the original can't be rebuilt exactly. JPEG and MP3 use it.

27permanent loss

Data removed by lossy compression is gone for good, so the original quality cannot be restored. Keep the original file, as re-saving or compressing again only lowers quality further.

28higher resolution and colour depth

Raising either one improves image quality (sharper detail, smoother colours) but stores more bits, so the file size gets larger.

29lossy image compression

Reduces an image's resolution or colour depth to shrink the file. Detail is lost for good. Recalculate width x height x depth to see the saving.

30higher sample rate or resolution

Raising the sample rate or sample resolution records the sound more accurately, but it also makes the audio file bigger. Lowering either does the opposite: less accurate, smaller file.

31lossy sound compression

Lowering the sample rate or sample resolution of a sound so it needs fewer bits. The file gets smaller, but the lost sound detail can never be recovered.

32bitrate

The number of bits used for each second of audio or video, measured in kbps. A lower bitrate gives a smaller file but lower quality, e.g. 128 kbps is smaller than 320 kbps.

33File > Export

Audacity menu path that saves a recording as WAV or MP3 at a chosen quality, so you can compare file size and sound quality of the same audio.

34inter-frame compression

Saves video space by storing only what changes between frames, reusing the still background from earlier frames and dropping fine detail viewers will not notice.

35adaptive bitrate

Streaming that lowers the bitrate of compressed audio and video on slow connections, trading quality for smooth playback with less buffering.

36lossy vs lossless

Lossy makes smaller files but permanently removes data; lossless keeps all data so the original can be restored, but saves less space.

37Compressed file format

A file type that stores data compressed: ZIP, PNG, FLAC are lossless; JPEG, MP3, MP4 are lossy. Each suits its content, such as photos, logos, music, video or documents.

38compression ratio = original size / compressed size

Original size divided by compressed size. Percentage saved = (original - compressed) / original x 100. Example: 10 MB down to 2 MB is a ratio of 5 to 1, saving 80%.

39Lossless vs lossy choice

Pick lossless (PNG, ZIP, FLAC) when every detail must be kept. Pick lossy (JPEG, MP3, MP4) when a smaller file matters more than perfect quality.

40because

Linking word in an explanation: name the technique, say how it shrinks the file, and state what is lost or kept, e.g. MP3 is smaller because it drops sounds you can't hear.