2. Point operations translate gray scale values on a pixel-by-pixel basis from one image to another.

3. Objective:-The goal of histogram equalization is to find and apply a point operation such that the histogram of the modified image approximates a uniform distribution.

4. Histogram is a discrete distribution & homogeneous point operations can only shift & merge(but never split) histogram entries, we only obtain approximate solution in general.

5. Brightness is to add a constant amount of light to the sample value in each position in the image raster.

6. Objective:-increase brightness(for 256 grayscale image) .

8. Objective :-inverse image (for 256 grayscale image).

10. Contrast modifications, logical operations and threshold are examples of this kind of operation.

12. In every operation first and second images are original and histogram.

13. The following third and fourth figures are modified image and it’s histogram respectively, which have been operated.

14. Threshold an image is the process of making all pixels above a certain threshold level white, others black.

15. Objective :-select pixels within boundaries(for 256 grayscale image).

17. Assume that alow & ahigh are the lowest &highest pixel values. found in the current image, whose full intensity rang is [amin,amax].

19. A solution :-fcontrast(a) =min{a×1.5 , 255}