Bit plane slicing is well known technique used in Image processing. In image compression Bit plane slicing is used. Bit plane slicing is the conversion of image into multilevel binary image. These binary images are then compressed using different algorithm. With this technique, the valid bits from gray scale images can be separated, and it will be useful for processing these data in very less time complexity.

Digitally, an image is represented in terms of pixels. These pixels can be expressed further in terms of bits. Separating a digital image into its bit-planes is useful for analyzing the relative importance played by each bit of image, a process aids in determining the adequacy of the no. of bits used to quantize each pixel. This type of decomposition is useful for image compression. This term of bit-plane extraction for an 8 bit image, it is not difficult to show that the (binary) image for bit-plane 7 can be obtained by processing input image with a thresholding gray-level transformation function.

### Overview of Bit Plane Slicing

Instead of highlighting gray level images, highlighting the contribution made to total image appearance by specific bits might be desired. Suppose that each pixel in an image is represented by 8 bits. Imagine the image is composed of 8, 1-bit planes ranging from bit plane1-0 (LSB) to bit plane 7 (MSB).

In terms of 8-bits bytes, plane 0 contains all lowest order bits in the bytes comprising the pixels in the image and plane 7 contains all high order bits.

#### Figure 1: Pictorial View of bit plane slicing

In terms of bit-plane extraction for a 8-bit image, it is seen that binary image for bit plane 7 is obtained by proceeding the input image with a thresholding gray-level transformation function that maps all levels between 0 and 127 to one level (e.g. 0)and maps all levels from 129 to 253 to another (e.g. 255).

The bit plane slicing is a fundamental technique of image processing in which the image is sliced into different planes (each layer contains sequences of only binary digits 0 or 1). It is ranges from plane1 which contains the least significant bit (LSB) to the last plane N which contains the most significant bit (MSB), where the number of layers depends on the bit depth of the image. The bit depth means how many bits need to represent the pixel’s intensity. For example if the image is grayscale then the bit depth is 8bit and it will be separated into 8 layers, or into 24 layers if the image is colored i.e. bit depth is 24bit.

### Example of Bit Plane Slicing

The gray level of each pixel in a digital image is stored as one or more bytes in a computer. For an 8-bit image, 0 is encoded as 00000000 and 255 is encoded as 11111111. Any number between 0 t0 255 is encoded as one byte. The bit in the far left side is referred as the most significant bit (MSB) because a change in that bit would significantly change the value encoded by the byte. The bit in the far right is referred as the least significant bit (LSB), because a change in this bit does not change the encoded gray value much. The bit plane representation of an eight-bit digital image is given by:

#### Figure 2: Bit-plane Slicing

Bit plane slicing is a method of representing an image with one or more bits of the byte used for each pixel. One can use only MSB to represent the pixel, which reduces the original gray level to a binary image. The three main goals of bit plane slicing is

- Converting a gray level image to a binary image.
- Representing an image with fewer bits and corresponding the image to a smaller size
- Enhancing the image by focusing

Bit plane slicing

Since the given image has a maximum grey level of 7, it is a 3-bit image. We convert the image to binary and separate the bit planes.

Separating the bit planes, we obtain

#### MSB Plane

####

Centre bit plane

#### LSB Plane

### References

[1] Bit-plane slicing, available online at: http://nptel.ac.in/courses/117104069/chapter_8/8_13.html

[2] Hassan K. Albahadily, V. Yu. Tsviatkou and V.K. Kanapelka, “Grayscale Image Compression using Bit Plane Slicing and Developed RLE Algorithms”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 6, Issue 2, February 2017

[3] Arjun Nichal, “How to Implement Bitplane slicing in MATLAB”, Wednesday, 27 November 2013, available online at: https://imagelpcmatlab.blogspot.in/2013/11/how-to-implement-bitplane-slicing-in.html

[4] Bit plane slicing, May 2013, available online at: http://www.ques10.com/p/5922/short-note-bit-plane-slicing-1/

## 2 Comments

I want to show my appreciation to the writer just for rescuing me from such a trouble. As a result of checking throughout the internet and coming across recommendations which were not powerful, I believed my life was done. Being alive without the presence of approaches to the difficulties you have fixed through your good short post is a crucial case, as well as the ones which could have badly affected my entire career if I hadn’t discovered the website. Your primary competence and kindness in maneuvering all the stuff was important. I’m not sure what I would’ve done if I hadn’t come upon such a subject like this. I can also at this moment relish my future. Thank you very much for the expert and sensible guide. I will not be reluctant to recommend your web site to any person who should receive support on this subject.

Good work and easy to understand