but knowing where your head is it is probably hard to remove it and think clearly.
But it clearly stinks, am I right?
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But it clearly stinks, am I right?
But it clearly stinks, am I right?
It ain't latex...
bob
It's better to have two hands than one glove.
Lossy is the term used to describe a file format that when it saves it discards information during the saving process. JPG and MP3 are 2 examples. I did not make this up. Compressed TIFF files are not lossy, as in there is no discarded information. If you were not so busy trying find ways to be rude and belittle others you could actually learn something, but knowing where your head is it is probably hard to remove it and think clearly.
Any compression algorithm discards data, if it didn't it wouldn't be a compression algorithm. Some compression processes reconstruct the original data with more fidelity than others. Some sacrifice fidelity for size. The point is that with bitmaps for the most part you can tolerate a great deal of reconstruction via interpolation or whatever without it being particularly noticeable.
Tell you what sport, I'll create both a jpg and a tif from some image or another and I'll print them both in identical environments. If you can tell which was the tif and which was the jpg without instrumentation I'll kiss your as$ in the middle of the street and give you a 1/2 hour to draw a crowd. Note that telling which is which does not include guessing, a 50:50 proposition, but by giving specific discernible criteria for your choice.
Actually there is LOSSLESS compression. It will not lose any data. Like TIFF compression.
You may be unable to tell the difference, but knowing there is information about the colour or sharpness of my image being removed, no matter how small or insignificant to you it may seem, to me why would I ever work in a format that is throwing away the quality of my image.
As far as your invitation to a date, I only like girls, so you won't be kissing me in the street ever. You can freely do what you want, just do it with someone of your own persuasion.
PS- If you are using JPG, be sure to have chroma subsampling turned off.
bob
It's better to have two hands than one glove.
Are you deliberately obtuse or are your really as simple as you appear? In your own example above, twenty five 1's were lost in compression. That they may or may not be recreated later with whatever fidelity is not germane. Inarguably the original data was discarded.
Moreover you picked a bit of a straw man for an example what with using '1's thus implying the only other value would, most likely, be '0'. A bitmap isn't a binary proposition where the loss or gain of a single 1 or 0 is easily detectable. Each pixel in an RGB bit map, assuming a normal 24 bit color depth, allows for 16,777,216 values per pixel. Do you really think that you or anyone else on this planet could detect one part in over 16,000,000 without instruments? So what if your compression algorithm ends up changing a some 7,345,872 values to 7,345,871?
Yes, a tif will reconstruct the image with pixel by pixel fidelity and yes, a jpg does not necessarily do so. The point is that either way the resultant images are visually identical. That being the case , why would anyone pack around bloated tif files other than to service their own delusions?
Bob I was showing an example of how compression could work. When decompressed, there would be once again 26 1's. A JPG may or may not recreate all the 1's.
Have you ever watched an MP3/MP4 movie online? Notice how the night scenes show up blocky? That's because the compression limits the number of grey shades. The complete gamut has been reduced, the colour info deleted forever.
I have an i7 64 bit, SSD dual drive 32 gig ram PC. I have no problem handling large TIFF files.
I get that you cannot see the difference. Maybe/probably there is no loss the way you work. For me I would rather deal with TIFF files than work in lossy formats. Each to his own.
Peace bro.
Have you ever watched an MP3/MP4 movie online? Notice how the night scenes show up blocky? That's because the compression limits the number of grey shades. The complete gamut has been reduced, the colour info deleted forever.
I have an i7 64 bit, SSD dual drive 32 gig ram PC. I have no problem handling large TIFF files.
I get that you cannot see the difference. Maybe/probably there is no loss the way you work. For me I would rather deal with TIFF files than work in lossy formats. Each to his own.
Peace bro.
De.signs Nanaimo
New Member
In the end it is more about prefered work flow that 98% or 100% quality of the image, we have all blown stuff out the front door of the shop that is less than ideal. I fail to see the reason to insult someone over their choice of image, the resulting print quality only affects their own business and their bottom line. Disagree yes, but insults get you nothing in return but your own negative energy thrown right back in your face. It's like watching someone throw nails in the air over their own head, and then they wonder why they keep getting nailed!
Techman
New Member
If any one understands anything about compression of images.. They will not be arguing about the merits of data...
Compression is the stripping out and simplifying of information
Most bitmap images cannot be compressed all that much. That is why an image compressed with some routines will not reduce in size very much.
Compression routines look for like (similar) data and set a code for that data. For example the word "the" is found and a code set then the routine looks for more instances of the word "the" and strips them out. Then throws away that data. The idea is to later reconstruct the data from the code.
The challenge is... The tolerances set in that data comparison routine may be variable. Taking number 1 and compressing it is useless because it is easy to compress. Set code for one and strip all the rest.. when restored it is still a 1.
If the tolerance .9 to 1.1 it will grab that,, set a code for 1 and throw away the base data.
When it reconstructs the image it will set that data as 1.. As one can see there is an average that has errors. Thus artifacts in an opened jpg after several savings..
The saying is easy to compress hard to compare.
Therefor there is a loss of data in compression..
Compression is the stripping out and simplifying of information
Most bitmap images cannot be compressed all that much. That is why an image compressed with some routines will not reduce in size very much.
Compression routines look for like (similar) data and set a code for that data. For example the word "the" is found and a code set then the routine looks for more instances of the word "the" and strips them out. Then throws away that data. The idea is to later reconstruct the data from the code.
The challenge is... The tolerances set in that data comparison routine may be variable. Taking number 1 and compressing it is useless because it is easy to compress. Set code for one and strip all the rest.. when restored it is still a 1.
If the tolerance .9 to 1.1 it will grab that,, set a code for 1 and throw away the base data.
When it reconstructs the image it will set that data as 1.. As one can see there is an average that has errors. Thus artifacts in an opened jpg after several savings..
The saying is easy to compress hard to compare.
Therefor there is a loss of data in compression..