"Counting what ? I'm still not clear by what process you determine that one picture composed of random pixels is a genuine picture of the past.....and another picture composed of random pixels isn't.
Also.....2^262144 is VASTLY more than a petabyte ( a quadrillion ). A quadrillion is actually a mere 2^50.
In fact, you will find that 2^262144 is not that much different to my original 10^65536......as though you only have one fifth of the pixel colours.....you have 4 times the area in your pic.
All the hard drives in a trillion universes will not hold that much data."
1) they are not random.
2) yes it is more than a petabyte, but you still have not read the site I linked to in the original post as you would realise that we would for a start only output half the total combinations as beyond a certain point each further combination is an inverse of a previously output one. There are many other things you can do to improve performance and storage requirements.
Darby,
You are correct I do not care what you think. It is obvious from your reply that you are not even digesting what is written rather rushing to voice your opinion. If you actually read my response and use of 2^ 262144 you would notice that this is 2 to the power of the total pixels of a 512x512 image (262144) giving the total combinations of that set size. Also you use the universe as an example giving its apparent total count of sub-atomic particles as some kind of reasoning as to why I cannot manipulate representations of visible light in combination in time, actually I cannot even be bothered, believe what you will.
Twilight,
Forget all the multi-verse and multiple timeline stuff and just answer me one question, do you believe that the images that have and are yet to be taken of this universe and its single timeline can be represented in a digital system? If so isn’t it obvious you have a version of a time machine you just lack the ability to use it correctly.
I’m going to continue on now and begin to explain some things.
I just wish to clarify that I am not in support of a simple counting system but as that is as far as most people have developed in their understanding of this subject of VTT I will demonstrate some techniques to improve the requirements to output and store visuals.
Early in 2001 I started to delve into image/video compression and have since that time developed many techniques, the first I will outlay here is the foundation upon which all further developments of my own as to processes of compressing data are built.
For this example we will assume we are working in the RGB colour system, this system uses three numerical values with magnitude 0-255 to represent each of the primaries of Red Green and Blue. This colour system is simply radix or base 256, for this reason at this moment we will ignore the visual representation to concentrate on the numerical system underlying it.
Base 2 – Read right to left
…|128|64|32|16|8|4|2|1
Base 10 – Read right to left
…|1000000|100000|10000|1000|100|10|1
Base 256 – Read right to left
…|72057594037927936|281474976710656|1099511627776|4294967296|16777216|65536|256|1
I will just point out something that may not be immediately noticed, each larger base is a form of compression of the bases below it. An example:
1,0,1,0,1,0,1,0,0,0,1,0,0,1,0,1,0,0,0,0,1,1,0,0,1,1,0,1,0,0
To Base 10
713638708
To Base 256
42,137,67,52
The point to note here is that the compression is dependent on the amount of data to compress, for instance in the conversion from base 10 to base 256 there is not as drastic an improvement as there is from base 2 to base 10, however if you were to increase the amount of data to be interpreted to base 256 we would notice a larger change. For instance to represent the base 10 value of 281474976710656 in base 256 would be 1,0,0,0,0,0,0 which interprets as follows
281474976710656|1099511627776|4294967296|16777216|65536|256|1
_____________1_____________0__________0________0_____0___0_0
This knowledge can be used to improve the compression of data required to explain a visual, thus decreasing the amount of storage required. I will cover the details of this shortly but first I want to offer what I would consider to be a fresh perspective as to how an image is understood. It is typically explained that an image is constructed from an array of numerical values each of which may represent wholly or when used in combination a pixel. An example:
{0,255,76,83,196,245} this is a numerical array representing the values of a two pixel RGB image as is shown below.
My proposition: Rather than interpreting the values of this image as representing the pixels, interpret the total value as an index of an array. This will be easier understood returning to black and white imaging. Below is listed every combination available for a two pixel B&W image.
00
01
10
11
For the moment we will ignore colour tables and pixel indexing and assume these combinations as images would be sent as they are, perhaps they would include a header to identify the file type as well as the width and height of the image and then the pixel colours (Represented here as 0 and 1) So someone might send you the image 01 and it might arrive as such:
HEADER|WIDTH|HEIGHT|0|1
Instead of this system I would instead state that each of these images can be accessed via index.
00 – index = 0
01 – index = 1
10 – index = 2
11 – index = 3
So instead of
HEADER|WIDTH|HEIGHT|0|1
we would have
HEADER|WIDTH|HEIGHT|1
Obviously this does not seem like much of an improvement but remember we are dealing with very low resolution images in this example and the compression ratio will increase as the amount of data does. The next point to note is that we are using radix 10 for the indices; this unfortunately will not work because as we know there are more than billions of indexes and for those who are into programming we know we only have the ability to work with unsigned and signed integers of certain bit sizes (Not including custom types, though they still have restrictions). It is for these reasons we perform some numerical trickery, instead using a larger base that can be interpreted within system to an index of the indicated resolution. I will leave this here and pick it up when I can.