IT6005 DIP Important Questions, Digital Image Processing Answer Key – ECE 7th SEM

IT6005 DIP Important Questions

Anna University Regulation 2013 ECE IT6005 DIP Important Questions with Answer Key and ECE 7th SEM IT6005 Digital Image Processing Engineering Answer Key is listed down for students to make perfect utilization and score maximum marks with our study materials.

UNIT II IMAGE ENHANCEMENT

PART-A

1. Specify the objective of image enhancement technique.

The objective of enhancement technique is to process an image so that the result is more suitable than the original image for a particular application.

2. Explain the 2 categories of image enhancement. (Dec’12)

     i) Spatial domain refers to image plane itself & approaches in this category are based on direct manipulation of picture image.

      ii) Frequency domain methods based on modifying the image by fourier transform.

3. What is contrast stretching? (Dec’13)

Contrast stretching reduces an image of higher contrast than the original by darkening the levels below m and brightening the levels above m in the image.

4. What is grey level slicing?

Highlighting a specific range of grey levels in an image often is desired. Applications include enhancing features such as masses of water in satellite imagery and enhancing flaws in x-ray images.

5. Define image subtraction.

The difference between 2 images f(x,y) and h(x,y) expressed as g(x,y)=f(x,y)-h(x,y) is obtained by computing the difference between all pairs of corresponding pixels from f and h.

6. What is the purpose of image averaging?

An important application of image averaging is in the field of astronomy, where imaging with very low light levels is routine, causing sensor noise frequently to render single images virtually useless for analysis.

7. What is meant by masking?

Mask is the small 2-D array in which the values of mask co-efficient determines the nature of process. The enhancement technique based on this type of approach is referred to as mask processing.

8. Define histogram.

The histogram of a digital image with gray levels in the range [0, L-1] is a discrete function h(rk)=nk. rk-kth gray level; nk-number of pixels in the image having gray level rk.

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