downscale large 1 bit tiff to 8 bit grayscale / 24 bit
Let's say i have a 100000x100000 1 bit (K channel) tiff with a dpi of 2000 and i want to downscale this to a dpi of 200. My resulting image would be 10000x10000 image. Does this mean that every 10 bits in the 1 bit image correspond to 1 pixel in the new image? By the way, i am using libtiff and reading the 1 bit tiff with tiffread开发者_开发问答scanline. Thanks!
That means every 100 bits in the 1 bit image correspond to 1 pixel in the new image. You'd need to average the value over 10x10 1bit pixel area. For smoother greyscales, you'd better average over n bits where n is the bit depth of your target pixel, overlying the calculated area partially with neighbor areas (16x16px squares 10x10px apart, so their borders overlay, for a smooth 8-bit grayscale.)
It is important to understand why you want to downscale (because of output medium or because of file size?). As SF pointed out, colors/grayscale are somewhat interchangeable with resolution. If it is only about file size losless/lossy compression is also worth to look at..
The other thing is to understand a bit of the characteristics of your source image. For instance, if the source image is rasterized (as for newspaper images) you may get akward patterns because the dot-matrix is messed up. I have once tried to restore an old news-paper image, and I found it a lot of work. I ended up converting it to gray scale first before enhancing the image.
I suggest to experiment a bit with VIPS or Irfanview to find the best results (i.e. what is the effect of a certain resampling algorithm on your image quality). The reason for these programs (over i.e. Photoshop) is that you can experiment with GUI/command line while being aware of name/parameters of the algorithms behind it. With VIPS you can control most if not all parameters.
[Edit] TiffDump (supplied with LibTiff binaries) is a valuable source of information. It will tell you about byte ordering etc. What I did was to start with a known image. For instance, LibTIFF.NET comes with many test images, including b&w (some with 0=black, some with 1=black). [/Edit]
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