Data how much of it is stored
This presentation is the property of its rightful owner.
Sponsored Links
1 / 22

Data – How (Much of) It Is Stored PowerPoint PPT Presentation


  • 56 Views
  • Uploaded on
  • Presentation posted in: General

Data – How (Much of) It Is Stored. Outline. What Is an Image Really? Methods of Storing Images How to Make a Big File Small Compression Algorithms Conversion Algorithms In theory In practice. What is an image?.

Download Presentation

Data – How (Much of) It Is Stored

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Data how much of it is stored

Data – How (Much of)It Is Stored

CS 128/ES 228 - Lecture 7a


Outline

Outline

  • What Is an Image Really?

  • Methods of Storing Images

  • How to Make a Big File Small

  • Compression Algorithms

  • Conversion Algorithms

    • In theory

    • In practice

CS 128/ES 228 - Lecture 7a


What is an image

What is an image?

  • An image is anything we store on the computer that we think of as a “picture”. It should look “the same” on any display.

  • Image file formats

    • GIF, JPEG, TIFF, BMP

    • NOT shapefiles

CS 128/ES 228 - Lecture 7a


File formats

File Formats

  • There are many image file formats

    • 35 on the first page I hit looking for a list!

  • Each has advantages and disadvantages

CS 128/ES 228 - Lecture 7a


Data how much of it is stored

GIF

  • Developed by Compuserve in 1987

  • Particularly good for line drawings (anything with sharp edges)

  • VERY common on web

CS 128/ES 228 - Lecture 7a


Jpeg or jpg

JPEG (or JPG)

  • Product of the Joint Photographers Experimental Group

  • Good for photos, images with subtle changes

  • Also popular on the web

CS 128/ES 228 - Lecture 7a


Gif vs jpeg

GIF vs. JPEG

CS 128/ES 228 - Lecture 7a


Jpeg 2000 aka jp2

JPEG 2000 (aka JP2)

  • “The JP2 and JPX file formats allow for handling of color-space information, metadata, and for interactivity in networked applications as developed in the JPEG Part 9 JPIP protocol.”

  • Some imagery is now distributed as JP2 files – datum and projection included at no extra charge!

CS 128/ES 228 - Lecture 7a


Portable network graphics png

Portable Network Graphics (PNG)

  • PNG also stands for “PNG’s Not GIF”

  • Loss-less compression using non-patented algorithm

  • Supports transparency, but not really animation

  • ISO standard since 2003

CS 128/ES 228 - Lecture 7a


Data how much of it is stored

BMP

  • Bitmap format –

    Primarily for Windows (but not exclusively)

  • NO Compression means LARGE files

  • Standard Screen Snapshot is BMP

CS 128/ES 228 - Lecture 7a


Eps pict tiff

EPS, PICT, TIFF

  • Encapsulated PostScript (mostly for printing, some display)

  • PICTure format (Macs only)

  • Tag Interchange File Format (multi-platform, but less used these days)

CS 128/ES 228 - Lecture 7a


Shapefiles and active software

Shapefiles and active software

  • A running program may read from or write to these formats, but generally uses its own memory management while running.

  • Shapefiles contain shape information and are not in any of these formats – and not truly image files

    • They are vector layers, after all

CS 128/ES 228 - Lecture 7a


Compression algorithms

Compression Algorithms

  • Compression algorithms “shrink” files

  • May do so by mathematical “tricks” or by discarding information

CS 128/ES 228 - Lecture 7a


Two key facts about compression

Two KEY Facts about Compression

  • NO LOSS-LESS compression algorithm can work all the time!

  • NO LOSSY compression algorithm can regenerate its original data.

CS 128/ES 228 - Lecture 7a


An loss less example run length compression

3 7

0 3 1 1 2 3 4 1 6

An LOSS-LESS ExampleRun-length compression

  • Count and record the length of the data set and then each group of 0’s or 1’s

1110100

1110000

1000000

CS 128/ES 228 - Lecture 7a


A lossy example truncation

124 029 935

725 304

A LOSSY ExampleTruncation

1242144903

0293570214

9352109521

7259027565

3048282535

1240000000

0290000000

9350000000

7250000000

3040000000

CS 128/ES 228 - Lecture 7a


How much does compression affect image quality

How much does compression affect image quality?

Original (32 MB)

Compressed(493 kB)

CS 128/ES 228 - Lecture 7a


Converting vector to raster

Converting Vector to Raster

  • Must compute the equation of the line

  • Then choose which pixels to highlight

  • Many algorithms, but differences are technical

CS 128/ES 228 - Lecture 7a


Typical algorithm

X = x0 Y = y0

(x1,y1)

Illuminate pixel (x, int(Y))

Y = y0 + 1

Illuminate pixel (x, int(Y))

X = X + 1 /m

Y = Y + 1

Illuminate pixel (x, int(Y))

(x0,y0)

Until Y == y1

Typical algorithm

CS 128/ES 228 - Lecture 7a


Anti aliasing

Anti-aliasing

Basic idea – Remove the “jaggies” by using color variations

CS 128/ES 228 - Lecture 7a


Conversion in practice

Conversion in practice

CS 128/ES 228 - Lecture 7a


Converting raster to vector

Converting Raster to Vector

  • Basic idea

    • Find areas with sharp changes – these are your boundaries.

    • Adjust as topology indicates

  • Much harder in practice than the other way around

  • Alternative is hand-digitization

CS 128/ES 228 - Lecture 7a


  • Login