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For example in audio codecs like Opus, MDCT is used with 50% percent overlap to avoid ringing artifacts. Why a similar approach is not used in image codecs. e.g., JPEG uses non-overlapping 8x8 blocks ?
Later lossy image codecs like JPEG2000 do use overlapped transforms, but these techniques just weren't around when JPEG was being defined. The wavelet transform that JPEG2000 is based on hadn't been invented yet, and time-domain anti-aliasing techniques like MDCT were extremely new.
For the MDCT in particular, as far as I know it is not used for image compression at all, even Today. I would guess that's because its basis vectors are asymmetric, which makes it intuitively difficult to choose for imaging applications.
I am trying to compress and resize DSLR camera photos. But my observation so far is that webp has noticeable degraded quality when webp file size is about 30% smaller than JPEG.
Command used to generate webp using imagemagick:
convert 1.JPG -strip -quality 80 -resize 800 -define
webp:method=6 1.webp
My goal is to get webp format that is at least 20% samller file size than JPEG while having virtually no difference in quality between JPEG and webp.
Is this achievable or again there is no such thing as free lunch?
Update Since the time of the original posting, I've discovered that using Google's cwebp compressor shows dramatically improved compression over ImageMagik 6.7.8, which is what powered my initial tests. This is especially true for images with transparency when compared to PNGs. Files using the mac version of the webp command (which uses cwebp under the hood) are about 1/4 of the size of the same file compressed with ImageMagik, and do provide a significant performance boost.
According to Google, "WebP typically acheives an average of 30% more compression than JPG" (source) with similar visual quality to a JPG. However, as you suggest, there in never such a thing as a free lunch.
Quality
Quality is largely a subjective measure, but keep in mind that you're comparing a file compressed at quality 80 with a file that doesn't have that level of compression (at least, this is what I understand from your question). Just running the default conversion without specifying a lower quality may give you slightly smaller files without loss of visible quality. 20% smaller might be a bit much of an ask, though, but it may be achievable for certain images.
convert 1.JPG 1.webp # do not specify quality
Size
In practice, it depends a lot on your settings and your source images. For example, I recently ran this command on all jpg images in a folder on a website "in the wild":
convert filename.jpg -quality 80 -strip -define webp:lossless=false -define webp:method=6 filename.webp
The convert command on this particular server is powered by ImageMagick 6.7.8. Some files were dramatically smaller compared to the original JPGs, while others were actually larger. Overall, after running that command, the total file sizes of all JPG images was 49MB, while the total file size of all WebP images was 29MB. That's a pretty good savings, however, when I ran ImageMagick's JPG compression, it was even better:
convert filename.jpg -sampling-factor 4:2:0 -strip -quality 80 -interlace JPEG filename-new.jpg;
The size of all new jpgs in the directory was 21MB. Both are set to compress at quality 80, but the jpg compression appears to be better. This may have to do with some compression already on my set of test images and how that interacts with the WebP conversion process.
As I found, file sizes can even grow, usually if you are converting between lossy and lossless images. On the FAQ page linked above, Google claims: "this is mainly due to the colorspace difference (YUV420 vs ARGB) and the conversion between these."
tl;dr: In the wild, it may or may not improve file size depending on the type of images, if/how the source file was compressed, and what quality you set for the WebP. Visible degradation is harder thing to measure, but try setting a higher quality, or without specifying a quality at all.
Just to add a side-comment to #Pwpwpw's excellent answer, webp is a good PNG replacement, but not great as a JPG replacement.
It beats PNG because it has better lossless compression algorithm than libpng, and it has the great feature of allowing different compression settings for different channels. You can do lossless on the alpha but lossy on the RGB, for example, which is fantastic for overlays.
Against JPG it does less well. It uses the VP8 codec for lossy, which is only somewhat better than JPG.
I would take a look at HEIC. It uses the much more modern h.265 for lossy compression and typically beats JPG by a factor of two at the same quality. It's the format Apple are using by default on iOS now.
libheif have a nice demo here:
https://strukturag.github.io/libheif/
That's libheif, compiled to javascript and running in your browser. You can upload .heic to it and download as jpg. libheif have some basic command-line tools to encode and decode images.
It does sadly have some patent issues, you might need to be a little cautious.
update Looking further out, the current hope is AVIF: it's the same container format as HEIC (called HEIF, confusingly), but swaps the problematic h.265 compressor for AV1. AV1 is roughly equivalent to h.265, but is patent-free.
update for 2022 AVIF seems to be too slow to be practical, so now hope rests on JXL. It's fast, patent free, supports HDR, transparency, etc., and compression is as good as HEIC. Chrome has support, though it's behind a flag for now.
You are re-encoding lossy compressed jpeg; if you have access to the original raw files you should use them as master. Currently you are compressing noise (and other artefacts) introduced by the jpeg encoder so the WebP codec does not have access to the same information that was already lost at the jpeg encoding. Of course it will look worse.
In other words; you should encode the original image data, if possible. I'm aware that some cameras and equipment only outputs HEIC / JPEG and not RAW so you might be out of options - the best thing to do is to keep the JPEGs as JPEGs.
Just did a quick test with a high-res JPG from my DSLR camera converting to a 410x800 background picture for mobile using Photoshop CC 2020 (and the WebPShop plugin).
Lossless:
PNG 100%: 680 KB
JPG 12 (max): 428 KB
WEBP 100%: 537 KB
50% quality:
JPG 6 (50%): 119KB
WEBP 50%: 45KB
At 50% JPG has more detail, but quite comparable quality.
0 quality:
JPG 0 (min): 51KB
WEBP 0%: 6KB
At 0% WEBP is horrible. But imagine the lowest quality JPG, and that's bad image quality and WEBP definitely beats it at 50%, while still being smaller in file size. So for me.. that's free lunch.
I'm having a strange realization while working on a project I'm having.
I created a streaming solution where i stream a image with the resolution 480x640 totaling at 30’720 pixels, and every pixel contains 32bits of data and by my calculations this means that every frame totals to 1,2MB of data which means that 30fps would total to a 36MB/s line.
So to my question how does a streaming solution stream 30fps over f.ex 2mbit/s line?
I'm guessing that the same question can probably used to explain how a jpg image with a 480x640 resolution takes up <100KB
Compression is your friend.
I don't know the specifics of your solution, but a few assumptions can be made.
First off, even if you send each frame as a full frame, they should be compressed. Even lossless compression should get you some pretty good compression rates, but if you go with something lossy (like jpg) then you can get even more.
But that's not all you get. Any good video codec should provide significant compression as well. Parts of the image that don't change between frames don't need to be sent at all, and other parts can be compressed nicely too (I don't know much specifics about the compression used, but there's a lot of stuff that's done to compress it).
This all adds up to a lot of savings over sending a full 32bit bitmap for every frame.
Compression is a very broad topic. Just to get an idea, try reading the wikipedia page about image compression
As a very basic solution to your problem, I would personally jpeg-encode the first frame, then, jpeg-encode the differences between two consecutive frames.
For jpeg compression there are many libraries providing the functionality, without the need to implement it yourself.
If you are not so interested in the quality, you can also subsample the video, for example obtaining frames of resolution 240*320
I'm working with lots of camera's which capture in BG bayer pattern natively.
Now, every time I record some data, I save it to the disk in the raw bayer pattern, in an avi container. The problem is, that this really adds up after a while. After one year of research, I have close to 4TB of data...
So I'm looking for a lossless codec to compress this data. I know I could use libx264 (with --qp 0), or huffYUV, dirac or jpeg2000, but they all assume you have RGB or YUV data. It's easy enough to convert the bayered data to RGB, and then compress it, but it kind of defeats the purpose of compression if you first triple the data. This would also mean that the demoasicing artefacts introduced by debayering would also be in my source data, which is also not too great. It would be nice to have a codec that can work on the bayered data directly.
Even more nice would be that the solution would involve a codec that is already supported by gstreamer (or ffmpeg), since that's what I am already using.
A rather late suggestion, maybe useful for others..
It helps to deinterleave the Bayer pattern into four quadrants and then treat that image as grayscale. The sub-images (e.g. all red pixels in top left) have half the spatial resolution, but their pixels are more highly correlated. This leads to lower residuals from predictors using nearby pixels and therefore to better compression ratios.
I've seen this reach 2-3x lossless compression on 12-bit raw camera data.
If a commercial solution is ok, check out Cineform. I've used their sdk for a custom video compressor and it works great plus they have some great tools for processing the raw video.
Or if you prefer the open source route check out Elphel JP4.
All I know about Bayer Patterns I learned from Wikipedia, but isn't conversion to RGB more of a deinterlacing than a tripling? Doesn't the resolution for red and blue go down by a factor of 4 and green by a factor of 2? If so, a lossless image compression scheme like lossless jpeg might be just the thing.
This is really a two part question, since I don't fully understand how these things work just yet:
My situation: I'm writing a web app which lets the user upload an image. My app then resizes to something displayable (eg: 640x480-ish) and saves the file for use later.
My questions:
Given an arbitrary JPEG file, is it possible to tell what the quality level is, so that I can use that same quality when saving the resized image?
Does this even matter?? Should I be saving all the images at a decent level (eg: 75-80), regardless of the original quality?
I'm not so sure about this because, as I figure it: (let's take an extreme example), if someone had a 5 megapixel image saved at quality 0, it would be blocky as anything. Reducing the image size to 640x480, the blockiness would be smoothed out and barely less noticeable... until I saved it with quality 0 again...
On the other end of the spectrum, if there was an image which was 800x600 with q=0, resizing to 640x480 isn't going to change the fact that it looks like utter crap, so saving with q=80 would be redundant.
Am I even close?
I'm using GD2 library on PHP if that is of any use
You can view compress level using the identify tool in ImageMagick. Download and installation instructions can be found at the official website.
After you install it, run the following command from the command line:
identify -format '%Q' yourimage.jpg
This will return a value from 0 (low quality, small filesize) to 100 (high quality, large filesize).
Information source
JPEG is a lossy format. Every time you save a JPEG same image, regardless of quality level, you will reduce the actual image quality. Therefore even if you did obtain a quality level from the file, you could not maintain that same quality when you save a JPEG again (even at quality=100).
You should save your JPEG at as high a quality as you can afford in terms of file size. Or use a loss-less format such as PNG.
Low quality JPEG files do not simply become more blocky. Instead colour depth is reduced and the detail of sections of the image are removed. You can't rely on lower quality images being blocky and looking ok at smaller sizes.
According to the JFIF spec. the quality number (0-100) is not stored in the image header, although the horizontal and vertical pixel density is stored.
For future visitors, checking the quality of a given jpeg, you could just use imagemagick tooling:
$> identify -format '%Q' filename.jpg
92%
Jpeg compression algorithm has some parameters which influence on the quality of the result image.
One of such parameters are quantization tables which defines how many bits will be used on each coefficient. Different programs use different quatization tables.
Some programs allow user to set quality level 0-100. But there is no common defenition of this number. The image made with Photoshop with 60% quality takes 46 KB, while the image made with GIMP takes only 26 KB.
Quantization tables are also different.
There are other parameters such subsampling, dct method and etc.
So you can't describe all of them by single quality level number and you can't compare quality of jpeg images by single number. But you can create such number like photoshop or gimp which will describe compromiss between size on quality.
More information:
http://patrakov.blogspot.com/2008/12/jpeg-quality-is-meaningless-number.html
Common practice is that you resize the image to appropriate size and apply jpeg after that. In this case huge and middle images will have the same size and quality.
Here is a formula I've found to work well:
jpg100size (the size it should not exceed in bytes for 98-100% quality) = width*height/1.7
jpgxsize = jpg100size*x (x = percent, e.g. 0.65)
so, you could use these to find out statistically what quality your jpg was last saved at. if you want to get it down to let's say 65% quality and if you want to avoid resampling, you should compare the size initially to make sure it's not already too low, and only then reduce the quality
As there are already two answers using identify, here's one that also outputs the file name (for scanning multiple files at once):
If you wish to have a simple output of filename: quality for use on multiple images, you can use
identify -format '%f: %Q' *
to show the filename + compression of all files within the current directory.
So, there are basically two cases you care about:
If an incoming image has quality set too high, it may take up an inappropriate amount of space. Therefore, you might want, for example, to reduce incoming q=99 to q=85.
If an incoming image has quality set too low, it might be a waste of space to raise it's quality. Except that an image that's had a large amount of data discarded won't magically take up more space when the quality is raised -- blocky images will compress very nicely even at high quality settings. So, in my opinion it's perfectly OK to raise incoming q=1 to q=85.
From this I would think simply forcing a decent quality setting is a perfectly acceptable thing to do.
Every new save of the file will further decrease overall quality, by using higher quality values you will preserve more of image. Regardless of what original image quality was.
If you resave a JPEG using the same software that created it originally, using the same settings, you'll find that the damage is minimized - the algorithm will tend to throw out the same information it threw out the first time. I don't think there's any way to know what level was selected just by looking at the file; even if you could, different software almost guarantees different parameters and rounding, making a match almost impossible.
This may be a silly question, but why would you be concerned about micromanaging the quality of the document? I believe if you use ImageMagick to do the conversion, it will manage the quality of the JPEG for you for best effect. http://www.php.net/manual/en/intro.imagick.php
Here are some ways to achieve your (1) and get it right.
There are ways to do this by fitting to the quantization tables. Sherloq - for example - does this:
https://github.com/GuidoBartoli/sherloq
The relevant (python) code is at https://github.com/GuidoBartoli/sherloq/blob/master/gui/quality.py
There is another algorithm written up in https://arxiv.org/abs/1802.00992 - you might consider contacting the author for any code etc.
You can also simulate file_size(image_dimensions,quality_level) and then invert that function/lookup table to get quality_level(image_dimensions,file_size). Hey presto!
Finally, you can adopt a brute-force https://en.wikipedia.org/wiki/Error_level_analysis approach by calculating the difference between the original image and recompressed versions each saved at a different quality level. The quality level of the original is roughly the one for which the difference is minimized. Seems to work reasonably well (but is linear in the for-loop..).
Most often the quality factor used seems to be 75 or 95 which might help you to get to the result faster. Probably no-one would save a JPEG at 100. Probably no-one would usefully save it at < 60 either.
I can add other links for this as they become available - please put them in the comments.
If you trust Irfanview estimation of JPEG compression level you can extract that information from the info text file created by the following Windows line command (your path to i_view32.exe might be different):
"C:\Program Files (x86)\IrfanView\i_view32.exe" <image-file> /info=txtfile
Jpg compression level is recorded in the IPTC data of an image.
Use exiftool (it's free) to get the exif data of an image then do a search on the returned string for "Photoshop Quality". Or at least put the data returned into a text document and check to see what's recorded. It may vary depending on the software used to save the image.
"Writer Name : Adobe Photoshop
Reader Name : Adobe Photoshop CS6
Photoshop Quality : 7"