On 23/07/2020 16:33, Lloyd wrote:
We tried boost gil resize example to experiment with scaling down a jpeg
image file. For some images, this causes the size of the file to
increase. We are using bilinear_sampler algorithm.
Our aim to reduce the input image size so as to save storage/network
bandwidth. Quality can be compromised to a certain extent. Which
algorithm/method should we use?
Re-saving a JPEG file is pretty much always guaranteed to reduce
quality, no matter what settings you use.
The code fragment is given below:-
boost::gil::rgb8_image_t img;
boost::gil::read_and_convert_image(InStream, img, T());
float width = (float)(img.width() * Ratio) / 100;
float height = (float)(img.height() * Ratio) / 100;
boost::gil::rgb8_image_t resizedImg(width, height);
boost::gil::resize_view(const_view(img), view(resizedImg),
boost::gil::bilinear_sampler());
boost::gil::write_view(OutStream, boost::gil::const_view(resizedImg), T());
Probably the important part is what your T() is.
When calling write_view, you can specify a JPEG quality explicitly via
something like image_write_info<jpeg_tag>(95) -- use a lower number for
a smaller file size but more artifacting.
If you don't specify it, GIL uses 100 by default (which might be
excessive). Other editors probably use different values by default,
which might be causing the file size increase you're seeing.
But there isn't really one "right" answer, it depends on the specific
content of the image; values that will be acceptable for one image will
perform poorly on another. But depending on your usage you might be
able to safely go to 80-85% or perhaps even less.
The image quality isn't actually stored in the file (or when it is, it's
not always reliable), so you can't directly read what quality the image
was saved at -- although it is technically possible to read other data
to estimate it. I don't think GIL makes this information available,
however.
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