M.Sc. Computer Science SEM I 2023 2024 Feb 2024 APPLIED SIGNAL & IMAGE PROCESSING Question Paper - Mumbai University | munotes

Questions asked in this paper

• (2) Figures to the right indicate full marks

1. Q1 Attempt any two of the following 10 marks
   • a) Briefly discuss about various types of noise and its effect in Signal and Image 05
   • b) Define Correlation. How it useful in signal and image analysis. 05 Write a note on representing image as signal. 05
   • d) List and explain applications of digital signal processing. 05 Attempt any two of the following (10)
   • a) Compare log and power law transformation on the image. 05
   • b) Explain how histogram processing is useful in image processing. Explain the 05 terms histogram equalization and histogram matching Write a note on non-linear smoothing of images. Give example to explain the 05
   • d) Explain what is Contrast Stretching? How it is used to enhance images. 05 Attempt any two of the following (10)
   • a) List and explain Sobel and Prewitt edge detectors. 05
   • b) Briefly what are image pyramids? Also explain briefly Gaussian Pyramid. 05 Explain morphological opening and closing operations. What are its merits over 05 erosion and dilation operations?
   • d) Briefly explain how we can extract boundary of an object in an image. 05 Attempt any two of the following (10)
   • a) Briefly explain about scale-invariant feature transformations and its significance 05 in image processing
   • b) What is Haar-like Feature? Discuss in detail its use in image processing and 05 Write a brief note about the concept of using watershed algorithm for 05
   • d) Write a note on GrabCut algorithm in Image Processing. 05
2. Q5 Attempt any two of the following 10 marks
   • a) What is the effect of applying Laplacian on an image? Where is it used? 05
   • b) Write a note on LoG and DoG filters. 05 Define Skeletonization. Explain the operations and use of structuring elements 05 in skeletonizing the given object structure
   • d) Define Thresholding. Explain adaptive thresholding technique. 05

Read from the scan above, so a character or two may differ. The scan is the original.