This article is about the digital information term. For the company, see Bitplane.
The 8 bit-planes of a gray-scale image (the one on left). There are eight because the original image uses eight bits per pixel.
A bit plane of a digital discrete signal (such as image or sound) is a set of bits corresponding to a given bit position in each of the binary numbers representing the signal.[1]
For example, for 16-bit data representation there are 16 bit planes: the first bit plane contains the set of the most significant bit, and the 16th contains the least significant bit.
It is possible to see that the first bit plane gives the roughest but the most critical approximation of values of a medium, and the higher the number of the bit plane, the less is its contribution to the final stage. Thus, adding a bit plane gives a better approximation.
If a bit on the nth bit plane on an m-bit dataset is set to 1, it contributes a value of 2m−n, otherwise it contributes nothing. Therefore, bit planes can contribute half of the value of the previous bit plane. For example, in the 8-bit value 10110101 (181 in decimal) the bit planes work as follows:
Bit plane
Value
Contribution
Cumulative total
1st
1
1 × 27 = 128
128
2nd
0
0 × 26 = 0
128
3rd
1
1 × 25 = 32
160
4th
1
1 × 24 = 16
176
5th
0
0 × 23 = 0
176
6th
1
1 × 22 = 4
180
7th
0
0 × 21 = 0
180
8th
1
1 × 20 = 1
181
Bit plane is sometimes used as synonymous to Bitmap; however, technically the former refers to the location of the data in memory and the latter to the data itself.[2]
One aspect of using bit-planes is determining whether a bit-plane is random noise or contains significant information.
One method for calculating this is to compare each pixel (X, Y) to three adjacent pixels (X − 1, Y), (X, Y − 1) and (X − 1, Y − 1). If the pixel is the same as at least two of the three adjacent pixels, it is not noise. A noisy bit-plane will have 49% to 51% pixels that are noise.[3]
^"Bit Plane". PC Magazine. Archived from the original on 2012-10-07. Retrieved 2007-05-02.
^"Bit Plane". FOLDOC. Retrieved 2007-05-02.
^Strutz, Tilo (2001). "Fast Noise Suppression for Lossless Image Coding". Proceedings of Picture Coding Symposium (PCS'2001), Seoul, Korea. Retrieved 2008-01-15.
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