The programs done in Digital Image Processing lab 6th semester

1. Bit place Slicing - Pixel value of grayscale image lies between 0 -255, so its information is contained using 8 bit. So, we can divide those image into 8 planes (8 Binary Image). Binary image are those images whose pixel value can be either 0 or 1.
2. Contrast Streching - Contrast stretching as the name suggests is an image enhancement technique that tries to improve the contrast by stretching the intensity values of an image to fill the entire dynamic range. The transformation function used is always linear and monotonically increasing.
3. Distance Between 2 Points D4 - The city block distance metric measures the path between the pixels based on a 4-connected neighborhood. Pixels whose edges touch are 1 unit apart and pixels diagonally touching are 2 units apart.
4. Distance between 2 Points D8 - The chessboard distance metric measures the path between the pixels based on an 8-connected neighborhood. Pixels whose edges or corners touch are 1 unit apart.
5. Euclidian Distance - The Euclidean distance is the straight-line distance between two pixels.
6. Negation of Image - In the complement of a binary image, zeros become ones and ones become zeros. Black and white are reversed.
7. Thresholding - Image thresholding is a simple, yet effective, way of partitioning an image into a foreground and background.
8. Adding two Images - Z = imadd(X,Y) adds each element in array X with the corresponding element in array Y and returns the sum in the corresponding element of the output array Z.
9. Connected Components - CC = bwconncomp(BW) returns the connected components CC found in the binary image BW. bwconncomp uses a default connectivity of 8 for two dimensions, 26 for three dimensions, and conndef(ndims(BW),'maximal') for higher dimensions.
10. Gray Scale Slicing - Intensity level slicing means highlighting a specific range of intensities in an image. In other words, we segment certain gray level regions from the rest of the image.