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What is the difference between grayscale image and RGB image?
The RGB colour space You have 256 different shades of red, green and blue (1 byte can store a value from 0 to 255). So you mix these colours in different proportions, and you get your desired colour. And, the channels is a grayscale image (because each channel has 1-byte for each pixel).
What is the difference between the representation of a grayscale image and a black and white image?
Black and White image contains only two levels. Gray image represent by black and white shades or combination of levels for e.g. 8 bit gray image means total 2^8 levels form black to white 0 = black and 255 is White. Grayscale is a range of shades of gray without apparent color.
What is the difference between grayscale and binary images?
A binary image could be an image where pixels are only either red or blue. A binary image has only two values for each pixel, 0 and 1 corresponding to black and white (or vice versa). A gray scale image has a certain number (probably 8) bits of information per pixel, hence, 256 possible grey values.
How are MRI images converted to gray scale?
An algorithm can be written to make the addition of color information, but in general a color pattern cannot be extracted from the gray scales. MRI image is routinely converted to gray scale by assigning different arbitrary color values to different resonant frequencies.
How to convert MRI gray scale image to RGB in MATLAB?
If you filled the B channel with the Gray scale values and zero both R and G, you will get Blue shade image. You may copy the same values to the R, G and B, but this does not lead you to anything, i.e. you get the same gray image with RGB represented by 24 bit for each pixel instead of 8 in the old image.
How many bits are in a grey scale image?
A gray scale image has a certain number (probably 8) bits of information per pixel, hence, 256 possible grey values. Of course, a grey scale image has a binary representation, but the smallest size of information is not a bit, so we don’t call it a binary image.