Helpful for public speaking presentation

1. IMAGE COMPRESSION

9. RUN LENGTH CODING

16. PREDICTIVE CODING

19. BITPLANE SLICING
• Digitally, an image is represented in terms of pixels. Those
pixels can be expressed further as in terms of bits. As an
example, a pixel in 256-level grayscale image is comprised of
8 bits. So that we can have 8 bit planes for a single grayscale
image. A bit plane of a binary image is a set of bits
corresponding to a given bit position in each pixel value. It’s
possible to representing an image with one or more bits of
the byte used for each pixel. So this mechanism can be used
for Image Compression, Feature Extraction

21. • Bit-plane 1 is the lowest bit of the bit series and bit plane 8 is the
largest bit from the bit series Similar to this mechanism, images
have their separate bit planes for each and every pixel.
• Higher order bits contains most of significant visual information
• Lower order bits contains subtle details
• For an 8-bit image, a pixel value of 0 is represented as 00000000 in
binary form and 255 is encoded as 11111111. Here, the leftmost
bit is known as the most significant bit (MSB) as it contributes the
maximum. e.g. if MSB of 11111111 is changed to 0 (i.e. 01111111),
then the value changes from 255 to 127. Similarly, rightmost bit is
known as Least significant bit (LSB).

22. • In Bit-plane slicing, we divide the image into bit planes. This
is done by first converting the pixel values in the binary form
and then dividing it into bit planes. Let’s see by an example.
• For simplicity let’s take a 3×3, 3-bit image as shown below.
We know that the pixel values for 3-bit can take values
between 0 to 7.