Image Processing

A NOTE ON IMAGE PROCESSING

Consider the image of a building given below. This color image is decomposed as Red, Green and Blue images.

Converts RGB values to grayscale values by forming a weighted sum of the R, G, and B components:

0.2989 * R + 0.5870 * G + 0.1140 * B

age, the white represents the highest concentration of pure red values. As red becomes mixed with green or blue, gray pixels appear. The black region in the image shows pixel values that contain no red values, i.e., R == 0.

Fig. 1

Notice that each separated color plane in the figure contains an area of white. The white corresponds to the highest values (purest shades) of each separate color. For example, in the Red Plane image, the white represents the highest concentration of pure red values. As red becomes mixed with green or blue, gray pixels appear. The black region in the image shows pixel values that contain no red values, i.e., R == 0.

Fig. 2 Grayscale Image of 1.a

The histogram of the image is shown below

Fig.3 Histogram of fig.2

We may spread the intensity values over the full range of the image, a process called histogram equalization. The histogram equalized image is shown below.

                                                              Fig.4 Histogram Equalized of fig.2

                                                           Fig.5 Histogram of fig.4

DETECTING THE EDGES

Apply the Sobel and Canny edge detectors to the image and display them.

BW1 = edge(I,'sobel');

Fig. 6 Edges of fig 2 detected using Sobel method

Secondly Canny edge detection is tried.

Fig. 6 Edges of fig 2 detected using Canny method

The most powerful edge-detection method that edge provides is the Canny method. The Canny method differs from the other edge-detection methods in that it uses two different thresholds (to detect strong and weak edges), and includes the weak edges in the output only if they are connected to strong edges. This method is therefore less likely than the others to be fooled by noise, and more likely to detect true weak edges

Assignment Questions

1. Image restoration is the                             

2. MPEG stands for ----------------

3. Basic unit of a picture is called       ---------------------                   

4. Quantization error is called      --------------------------

5. ------------------ is a fast method to find 2D –Fourier  transforms.

6. Low pass filtering is used for image                                                                                                                                                       a) smoothing,  b)sharpening,  c)masking,  d)averaging.

7. Region growing is employed for -------------------------------                    

8. A high pass filter =original -                          .

    ( a)LPF, b) BDF, c) BSF, d) high boost filter)

9. Overshoot effects of bright bands in dark region and dark bands in bright region of human eye perception are called  -------------------  effect.

11. MPEG is an --------------------------  standard.

12. For processing of an image which Fourier transform is used?                               
a)1-D, b) 2-D).

13. Thresholding is a method used for                                                                                                                                           (image enhancement, image restoration, image segmentation, image compression).

14. What is histogram? What information it gives?

15. What is region merging?

16. Define 2D-DFT. List any two properties of 2D-DFT.

17. What are smoothing filters? Explain.

18. Briefly explain edge detection.

19. Explain the relevance of image thresholding.

20. Explain image segmentation.

21. Show that crispened image can be obtained by convolving it with matrix

                                                   0            -1              0

                                                   -1             5             -1

                                                    0            -1              0