Dan Williams // Name: Dan Williams
Location: Guildford, Surrey, UK
Born and raised in Somerset, I am a Computing student at Plymouth University currently on a year's placement at Allianz in Guildford. I enjoy football, technology, film and really want to go travelling next summer!!
Dijkstra's Algorithm - Interesting stuff especially when compared with the Bellman-Ford algorithm
Understanding image compression is really just a matter of thinking in numbers. The number of bits that are stored and the number of pixels that make up the image are key factors. An uncompressed image with a resolution of 640 x 480 pixels has 307,200 pixels total. A true color (24 bit) image of that size would take about 1 MB of storage space considering each pixel uses 3 bytes. The file size increases with the image resolution, for instance, if we have a true color image resolution of 1024 x 768 pixels, it's going to take 2.5 MB of storage space. Now, imagine that you have a few 2.5 MB files on your server that are downloaded by everyone who visits your web site... you would probably use up a lot of bandwidth quickly!
Thankfully, we can compress image data to make the file smaller while retaining the size of the image. There are a lot of programs that can convert and compress your images with ease, in fact, most image editors can. Also, most digital cameras compress your images automatically so you can store more images and move them to your computer quicker. Smaller image files are easier to manage which is why compressed images are ubiquitous. Images can be compressed in two ways, lossless and lossy. The difference between the two is that lossless files retain their data while lossy files lose data.
Lossless files like TIFF, GIF and PNG are saved using algorithms that reduce file size but do so without losing image quality. Unfortunately, the compression ratios are quite a bit weaker than lossy. That means that it will ultimately be a larger file, but the quality will be well preserved. Usually, images that will be printed are saved with a lossless compression because the integrity of the image is more important than viewing it on the Internet, for example.
Lossy files like JPEG and JPEG2000 discard information when they are saved. The amount of information that is discarded directly influences the size of the file. It's important to note that once you save a lossy file, you can never go back to the previous state. Each time the file is opened and saved as a JPEG, it will lose more and more data which will cause the image to become pixelated. The reason for this is that pixel data is trashed during compression and when the image is reopened, the computer must fill in the missing data by borrowing from neighboring pixels. This also happens when an image has been saved using a very high compression ratio for the same reason.
Low compression = Higher quality image
High compression = Lower quality image
I found this subnetting tutorial really helpful so anyone learning computer networks may want to have a look
A visual representation of rule 30 of cellular automata, an incredibly interesting subject which I am learning for my university course.
For more information check out: http://en.wikipedia.org/wiki/Cellular_automaton#Specific_CA_rules
A friend and I created this for a media project for part of my course last year and thought it would be cool to share :)
