I need convert an Android format (RGB 565) Image to RGB 24 format to avoid distraction when it displayed on computer. Any Suggestions? If someone can help me with an algorithm that'll be great.. Thanks
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I'm converting images with embedded ICC profiles to the sRGB color space using LittleCMS. I want to efficiently detect when this conversion is lossy due to the image containing pixels that are out-of-gamut for the sRGB (e.g. the image is using Display P3 and contains saturated colors).
Note that I don't want to merely check if the embedded profile has a wide gamut, because the image pixels may not be taking advantage of its full gamut, and still fit in sRGB.
I know there's cmsSetAlarmCodes, but this seems like it could cause false positives, because there's nothing stopping the image from actually containing the same color that I set for my alarm color. Does LCMS have some out of band signal for this?
Another approach that comes to my mind is applying conversion twice: to sRGB and then back to the original color space, and checking how lossy it was. But that more than doubles processing time. Is there a more efficient way?
I would like to convert a 3d image (hyperspectral cube) into a 2d one with 3 channels.
I have all images in the source and target – paired.
What should be changed in the code in order to support this?
(see good code with explanation here (Jason Brownlee):
https://machinelearningmastery.com/how-to-develop-a-pix2pix-gan-for-image-to-image-translation)
Thanks,
Eli
Does anyone know of a package in R that allows me to give several photographs the same average luminance?
The photographs I have are generally low definition. I have seen the package 'magick' but there is no mention of luminance as something that can be altered.
Although I am pretty new to the physics of light as I understand it luminance and brightness are different so altering the brightness is not quite enough.
Using imager, you can change the color space of an image (from RGB to HSL/HSV/HSI/YUV/YCbCR). In one color space, you can manipulate each channel as you like.
Here, I convert im from RGB to YUV (corresponding to one luma (Y) and two chrominance (UV) channels). Then, as an example, I incrementally increase the luma:
library(imager)
im <- load.image(system.file('extdata/parrots.png',package='imager'))
im.yuv <- RGBtoYUV(im) # convert from RGB to YUV
par(mfrow=c(1,3))
plot(im)
for (i in rep(0.2, 2)){
im.yuv[,,1,1] <- im.yuv[,,1,1] + i # the last dimension gives the channel; 1:Y 2:U 3:V
im.cor <- YUVtoRGB(im.yuv) # convert back from YUV to RGB
plot(im.cor)
}
I'm working on a spectroscopy project though its taking way too long. I haven't found any program online that can do what I need and I don't know how to do it myself. What I need is a program that takes an image(from the hard drive) and adds the rgb values in DEC out of 255 of every pixel, returned individually in red, green, and blue. Additionally, although I can do this part on my own, the values then need to be multiplied by 255 divided by the greatest value and converted to HEX as to retrieve a kinda total color of the entire image. (NOTE: I do not want an average color of the image, I tried that and it only returns neutral colors)
By googling for 2 minutes I found this:
https://itg.beckman.illinois.edu/technology_development/software_development/get_rgb/
No idea if it works but it looks like it does what you want.
I am currently doing an assigment and cannot find the answer to this question..as Algorithm is supposed to mean (solving problems as such)
The main difference is that JPEG uses a lossy algorithm, and GIF uses a losless algorithm (LZW). In addition, GIF is limited to 256 colors, while JPEG is truecolor (8 bits per color per pixel)
Some info is here.
Basically, JPEG is good for real life images, and GIF is good for computer generated images with solid areas or when you need some text to not be blurred (JPEG is lossy, GIF is not). There are many other differences too.
See also Wikipedia:
GIF
JPEG
For bonus points in your assignment you might want to mention other commonly used standards such as PNG.
i found a very good web site that explains about the difference between gif and jpeg plus it shows image examples of several scenarios. enjoy.
http://www.siriusweb.com/tutorials/gifvsjpg/