Solution:

(1) Brit plane slicing:

With this technique, the contribution made by each bit to the final image can be found.

Suppose that each pixel in an image is represented by 8 bits (for an 8-bit image).

If we group all $0^{\text {th }}$ proser all the pixels then we will get. $0^{\text {Th }}$ plane. If we group all list bitt of all the pixels then we will get $1^{\text {st }}$ plane Similarly we gat can do it for the remaining planes.

So we can say that for an 8-bit Image, the image has 8-bit planes.

The Ins $\left(7^{\text {th }}\right)$ plane consists of the most visually significant data. Other bit planes contribute to more subtle details in an Image. $0^{\text {th }}$ plane despot contain any signítlcant detail.

Separating a digital image into its bit planes is useful for analyzing the relative importance played by each p. bit of the image, Implying. It determines the adequacy of numbers of bits wed to quantize each pixel, useful for image compression.

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

(ii) Gray level slicing -

It is a point operation in the spatial domain. It is also known as intensity slicing. It is wed to highlight a particular part of the image. There are two methods -

1) With a background.

2) Without background.

$S=$ output gray level

$r=$ Input gray level

$L=$ gray level (highest-)

Fig shows the transformation function for gray level slicing without background.

$ \begin{aligned} &S=0 \\ &S=L-1 \end{aligned} $