The .jpg is an Internet favorite for a file format.

Let’s break it down. the .jpg is a bit different than the other formats I have covered so far. the biggest being that it is a. This means that some of the data we give the program is lost and ignored for the sake of simplifying the data for smaller compressed files. The .jpg is special, because it has closed source proprietary software that will look atThis is asimplification of the algorithm. It’s very effective, and fairly modular, so it’s wide spread use is no joke. The .jpg is probably your best bet for reducing a picture’s file size. In the early days of the Internet, that was a big deal!

The .jpg algorithm was designed around photography, where there are a lot of gradients, and curves. It’s very good at taking a photograph, and compressing it, where the lossy result is not that much visually different than the original. However, it’s very bad at reproducing fine, important details, especially at certain settings. It shouldn’t be used for things like screenshots of text.

those 8x8 chunks i mentioned before are going to be the crux of how we glitch the .jpg. The glitches will all exist and be visible in these chunks. However get ready to be disappointed.

Your standard .jpg has a large amount of bytes in the beginning that need to stay intact. changing them will result in your picture being completely unreadable in almost all cases.

The lame doesnt stop there. becasue the glitches are all confined to the chunks, most byte replacement glitches (where you are just altering random bytes) are going to just look like this.

But of course that’s not to say that all the results will be lame! No! quite the opposite! Your standard .jpg you download off the internet will probably be less interesting, but if you have access to a image editing software like Paint Shop Pro (what I use), Photoshop, or GIMP, then you can probably find the options that are associated witht he .jpg format.

EVERYONE LOVES OPTIONS, LETS GET TO THE GLITCHY FUNSTUFFS

agreed!

The pictures here are all glitched using a script i wrote in python. if you are feeling brave, and know what you are doing, feel free to get a copy here.

The most obvious option is the quality slider. In fact, just setting that down to small numbers can give a glitched look in itself.

This example is a compression factor of 99. You can see the picture has been mostly reduced to flat pixels, you will ocassionally find gradiented pixels, but not many. The colors have been reduced, and sloppily so. This image has not been byte replaced, so let’s see an example.

Not particularly different than your standard .jpg’s glitching. Changing the quality will not really result in anything other than a poopy picture. But that is not the only feature. so far, we have been using the Standard Encoding. This refers to the the order in which the data is saved and loaded as it streams to your computer. Let’s switch to Progressive Encoding.

It might look like it’s just pixelated, but it’s actually the same size. Remember when I said that the compression algorithm changed the picture into 8 x 8 chunks of different gradients? This glitching actually seems to cause the rebuilding algorithm (the one that changes the data back into a picture) to use the wrong gradients.) This property is really only visible on larger images. smaller images like this one behave differently.

Progressive encoding is actually pretty resistant. Small changes can ruin what the picture looks like up close, but it takes a lot to make the whole thing look crazy. this picture has 10 times the byte editing as the previous example. This picture actually shows off a stronger than normal example of one of the other features of the progressive encoding. I think the most interesting is the seeming ghosting. The chroma, and the values (colors and shading) don’t line up anymore. Also visible are colorful patches like in standard encoding, and the incorrect gradient being applied to squares.

This is the same settings, but on a larger image.

There is one more option, Chroma Sub Sampling. I have found that changing this does not result in anything spectacular in .jpg glitches. It does have an affect on the colors used, but it is very subtle. All these above images were made with the max Chroma Sub Sampling.

Well that was boring! Hey…. what’s this? JPEG2000?

Woah hey that’s cool! I am using a smaller image so that tumblr’s upload and resize doesn’t ruin the small details. This looks like a bunch of large noisy squares are invading the picture.

.jpg2000, or .jp2, is the sucessor to the .jpg by the JPEG. It works on a different compression algorithm, and isnt very widely used. It has the option of being lossy, or lossless. Their algorithms use wavelet compression, and are really just very heavy in math. I recommend the Wikipedia article if you are up for flexing your math muscle.

If you have an image editing software that supports .jp2, it is pretty fun to mess around with, but it features less options. Lossy and Lossless don’t seem to differ much in how they glitch, and many times, the output will just look like a blotchier version of the original

however, one option, the “save jpg2000 codestream” option, can be turned off for some more frequent intense effects.

Anyway. The .jpg can be goaded into being interesting, with a bit of persuasion! The picture used is The Gleaners, by Jean-François Millet