When I take pictures with my camera the file sizes seem exceedingly large. In this example the original is 5186kb. I wrote a java program to just read the image and then write it again, removing any information except the pixel values.
The first time it is rewritten, the file size goes down to 1005kb, over a 500% reduction! To make sure I wasn't losing data to compression I iterated the program 100 times on the resulting images and the file size stayed at exactly 1005kb with no loss in image quality.
My question is, what is the camera storing in the other 4181kb? Some sort of metadata I know, but it seems like a lot. I would like to know what I am losing by resizing my images like this.
Assuming the file format you are using is .jpg, the original file was saved in a higher value of jpg compression say 95%, while when you resave the file, you probably were using say 85% jpg compression value.
The size doesn't change in consequent saves as the compression value stays the same
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I wanted to scan Book pages and combine the images to an pdf "ebook" (just for me), but the file sizes get really huge. Even .jpg resulted in an pdf file with 60mb+ in size.
Do you have any idea how I can compress it any further? I.e. which file format I could choose for this specific purpose? (The book contains pictures and written text.)
Thank you for your help.
I tried to save it as .jpg and other file formats like .png, but didnt get small enough for the file to be easy handled, without loosing to much resolution.
Images are expensive things.
Ignoring compression you’re looking at 3bytes per pixel of data.
If you want to keep images you could reduce this by turning your images into greyscale. That reduces it to 1byte per pixel (again ignoring compression).
Or you could turn it into black and white. Which would be 1 but per pixel.
Or, alternatively, you could use OCR to translate your image into actual text which is a much more efficient way of storing books.
I thought this was a little odd.
Open Paint on Windows (I'm using Windows 7) and draw something (anything).
Then save as a .png for example called 1.png. Then save 'n' number of other copies straight away without modifying the image (2.png, 3.png,..etc).
I notice that 1.png has a different checksum to 2/3/4/../n.png.
1.png also varies in such (sometimes smaller and other times bigger) compared to the other images.
What is going on?
The difference in filesize is due to the choice of scanline filters used by the compressor. I don't have any idea why your application would use a different set of filters when compressing the image multiple times, but it's harmless.
There's no time stamp in the two images that Mohammad posted. According to "pngcheck -v", the only difference is in the content of the IDAT chunk. The image signatures computed by ImageMagick are identical. Neither image contains a tIME chunk.
"pngcrush" produces two identical images with a smaller filesize (11493 bytes).
According to "pngtest -mv" (pngtest is included in the libpng distribution), one image uses only the PNG "none" filter while the other uses the "none", "sub", and "up" filters.
The Wikipedia article on the PNG format seems to suggest there's a timestamp in there. That alone would do it.
Doesn't explain why subsequent files have the same checksum.
If I have a gif89a which has multiple image blocks that are identical (and small, say 40x40 or 1600 pixels in size), should these continue to increase the final size of the gif file (assuming a sane encoder)?
I'm trying to understand how the LZW compression works. According to the W3C spec, I thought the entire data stream itself (consisting of multiple image blocks) should be be compressed, and thus repeating the same image frame multiple times would incur very little overhead (just the size of the symbol for the the repeated image block). This does not seem to be the case, and I've tested with several encoders (Gimp, Photoshop).
Is this to be expected with all encoders, or are these two just doing it poorly?
With gimp, my test gif was 23k in size when it had 240 identical image blocks, and 58k in size with 500 image blocks, which seems less impressive than my intuition is telling me (my intuition's pretty dumb, so I won't be shocked if/when someone tells me it's incredibly wrong).
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I need to expand on what it is I'm getting at, I think, to receive a proper answer. I am wanting to handcraft a gif image (and possibly write an encoder if I'm up to it) that will take advantage of some quirks to compress it better than would happen otherwise.
I would like to include multiple sub-images in the gif that are used repeatedly in a tiling fashion. If the image is large (in this case, 1700x2200), gif can't compress the tiles well because it doesn't see them as tiles, it rasters from the top left to the bottom right, and at most a 30 pixel horizontal slice of any given tile will be given a symbol and compressed, and not the 30x35 tile itself.
The tiles themselves are just the alphabet and some punctuation in this case, from a scan of a magazine. Of course in the original scan, each "a" is slightly different than every other, which doesn't help for compression, and there's plenty of noise in the scan too, and that can't help.
As each tile will be repeated somewhere in the image anywhere from dozens to hundreds of times, and each is 30 or 40 times as large as any given slice of a tile, it looks like there are some gains to be had (supposing the gif file format can be bent towards my goals).
I've hand-created another gif in gimp, that uses 25 sub-images repeatedly (about 700 times, but I lost count). It is 90k in size unzipped, but zipping it drops it back down to 11k. This is true even though each sub-image has a different top/left coordinate (but that's only what, 4 bytes up in the header of the sub-image).
In comparison, a visually identical image with a single frame is 75k. This image gains nothing from being zipped.
There are other problems I've yet to figure out with the file (it's gif89a, and treats this as an animation even though I've set each frame to be 0ms in length, so you can't see it all immediately). I can't even begin to think how you might construct an encoder to do this... it would have to select the best-looking (or at least one of the better-looking) versions of any glyph, and then figure out the best x,y to overlay it even though it doesn't always line up very well.
It's primary use (I believe) would be for magazines scanned in as cbr/cbz ebooks.
I'm also going to embed my hand-crafted gif, it's easier to see what I'm getting at than to read my writing as I stumble over the explanation:
LZW (and GIF) compression is one-dimensional. An image is treated as a stream of symbols where any area-to-area (blocks in your terminology) symmetry is not used. An animated GIF image is just a series of images that are compressed independently and can be applied to the "main" image with various merging options. Animated GIF was more like a hack than a standard and it wasn't well thought out for efficiency in image size.
There is a good explanation for why you see smaller files after ZIP'ing your GIF with repeated blocks. ZIP files utilize several techniques which include a "repeated block" type of compression which could do well with small (<32K) blocks (or small distances separating) identical LZW data.
GIF-generating software can't overcome the basic limitation of how GIF images are compressed without writing a new standard. A slightly better approach is used by PNG which uses simple 2-dimensional filters to take advantage of horizontal and vertical symmetries and then compresses the result with FLATE compression. It sounds like what you're looking for is a more fractal or video approach which can have the concept of a set of compressed primitives that can be repeated at different positions in the final image. GIF and PNG cannot accomplish this.
GIF compression is stream-based. That means to maximize compression, you need to maximize the repeatability of the stream. Rather than square tiles, I'd use narrow strips to minimize the amount of data that passes before it starts repeating then keep the repeats within the same stream.
The LZW code size is capped at 12 bits, which means the compression table fills up relatively quickly. A typical encoder will output a clear code when this happens so that the compression can start over, giving good adaptability to fresh content. If you do your own custom encoder you can skip the clear code and keep reusing the existing table for higher compression results.
The GIF spec does not specify the behavior when a delay time of 0 is given, so you're at the mercy of the decoder implementation. For consistent results you should use a delay of 1 and accept that the entire image won't show up immediately.
I tried to change some pixel values of a Grayscale image and save it using imwrite in matlab.
no problem with saving.
the problem is when I read it back, some pixel values have been changed. not exactly the same values I assigned to pixels before saving it.
I'm trying to hash images so 1unit difference will effect the hash numbers.
As mentioned by mmgp, JPG can be lossy. That means that some of the information in your image will be lost in favor of storage efficiency.
The rationale behind JPG is somewhat like that behind MP3 -- changes in hues etc. that the human eye is not particularly well-adapted to distinguish will be simplified or removed altogether, thus decreasing the amount of information in the image. The information in a JPG represents a similar-looking, but in fact very different image. This is probably what you're experiencing.
In Matlab, have a look at the output of help imwrite. You can give a parameter to the jpg write called 'Quality', which is a number between 0 and 100, 100 meaning (near-)lossless compression.
Although the JPEG standard does allow for (near-)lossless compression, it is not often used in practice (at least, in my field). More popular lossless image formats are PNG, JPEG2000 and TIFF. Read more about it here.
All of these are also available in Matlab's imwrite function.
I'm porting some CF 2.0 VB.Net apps to a newer version of a handset that has twice the screen resolution. So I have to double the dimensions of everything otherwise it all gets squished up into the top LH corner of the screen.
One screen had a bitmap which was 250K in size, and after I doubled the dimensions naturally it blew out to one MB. This isn't real good on a handheld, so I fired up irfanview and converted it to a .GIF. The .GIF was only 60KB in size, with no discernible change in the quality of the image.
To me, it seems a no-brainer : Convert all Bitmaps to Gif (or JPG) and get the same results for a fraction of the disk space (and probably quicker form loading times).
But does anyone know of a situation where you would use a bitmap in preference to a GIF/JPEG? I cannot find any.
I really can't think of any realistic example where you would prefer an bitmap to a GIF. Since GIF is a lossless format you loose no information when storing images. So after reading the file in your app you will have the same image data as if you have read a bitmap. And like you said: The file will be smaller and thus will probably will be read faster from disk.
JPEG is different because it's a lossy format, meaning you will lose information when storing images in it. You will need to decide if the loss of information is meaningful in your app.
Bitmaps would be preferable if and only if reading files from disk where faster than decompressing the file in memory.
And to be precise you would prefer bitmaps when storing images in main memory, so you can work easily on the data in your code. Which is actually what you most likely already have when you have loaded a file using an image library.
To cut a long story shorts, a BMP is stored as a series of pixels along with their colour. This is useful if you want to do such things as pattern recognition, movement detection and such like.
Bitmaps are typically used for their convenience - you can knock one up in paint without having specialist graphics software.