मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) !योग सूची ( List of Practicals) सीएसई - तृतीय वष* / छठा सेमे0टर ( CSE - I II Year / VI Semester) स5 : जनवर: - जून , 202 6 ( Session: J an - June , 202 6 ) !डिजटल इमेज +ोसे.संग !योगशाला ( सीएसई - 3 25 ) , D igital Image Processing Lab (CSE - 325 ) " सं ( S. No.) +योग ( Practicals) लैब - १ (Lab - 1) Perform the following operations using library functions in PYTHON. 1. Read, Display and write any color image in various formats (e x - .jpg, .png, .tiff etc) 2. Find RED, GREEN and BLUE plane of the color image. 3. Create a color image from its RED, GREEN and BLUE planes. 4. Convert the color image into gray scale image. 5. Convert the color image into binary image. 6. Resize the image by one half and one quarter. 7. R otate the image by 45, 90 and 180 degrees. लैब - 2 (Lab - 2 ) 1. Perform sampling and quantization on a synthetic image and show the results at each stage. 2. Take an image of size 1024x1024 and find all the distances(D e , D 4 and D 8 ) between pixels at position (200,300) and (700,900). 3. Apply image Negation, L og transformation and Power law transformation with different values of gamma (+ve, - ve, 0, 1) on a synthetic image. 4. Perform intensity level slicing and bit level slicing. 5. Apply contrast stretching on a synthetic image. 6. Apply Histogram equalization on a synthetic image. लैब - ३ (Lab - 3 ) 1. Apply Histogram equalization on a synthetic image. 2. Create black and white images (A) of size 1024x1024. Which consists of alternative horizontal lines of black and white? Each line is of size 128. Create black and white images (B) of size 1024x1024. Which consists of alternative vertical lines of black and white? Each line is of size128. Perform the following arithmetic operations on Image A and Image B. a. Image addition of A and B b. Subtraction of A and B c. Multiplying Images of A and B d. Averaging Images of A and B 3. Create a grayscale image of size 256x1024. Intensity of image should vary sinusoidal. 4. Create a white image of size 256x256, with black box of size 58x58 at center. मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) लैब - ४ (Lab - 4 ) 1. W rite and execute programs to perform logical operations on any two grayscale images. a. AND operation between two images. b. OR operation between two images. c. Ex - OR operation between two images. d. NOT operation 2. Take a gray scale image and add salt and pepper noise. Write programs for following operations and observe their outputs a. M ean filtering b. Weighted Mean Filtering c. Median filtering. Compare the output quality among Mean Filtering and median filtering. 3. Write programs to perform following sharpening operations on a gray scale image a. Laplacian filter b. Unsharp masking c. High boost filtering लैब - ५ (Lab - 5 ) 1. Apply Fourier transform on a synthetic image and analyze the result Also apply inverse Fourier transform. 2. Develop programs to implement frequency domain smoothing /Low pass filters (Ideal, Butterworth and Gaussian) and apply these filters on a gray scale image. a. Compare/comment on the output of Ideal, Butterworth and Gaussian Low pass Filters having the same radii (cutoff frequency) value. b. Consider a suitable gray scale image and demonstrate the ringing effect on the output of Ideal low pass frequency domain filter. c. Compare the output of Butterworth low pass filters (order n=2) for different cut - off frequencies (5, 15, 30, 90, 120). d. Compare the output of Gaussian low pass filters for different cut - off frequencies (5, 15, 30, 90, and 120). 3. Develop programs to implement frequency domain sharpening/High pass filters (Ideal, Butterworth and Gaussian) and apply these filters on a gray scale image. a. Compare/comment on the output of Ideal, Butterworth and Gaussian High pass Filters having the same radii (cutoff frequency) value. b. Consider a suitable gray scale image and demonstrate the ringing effect on the output of Ideal high pass frequency domain filter. c. Compare the output of Butterworth high pass filters (order n=2) for different cut - off frequencies (5, 15, 30, 90, 120). d. Compare the output of Gaussian high pass filters for different cut - off frequencies (5, 15, 30, 90, and 120). मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) लैब - ६ (Lab - 6) 1. A dd following noise on a synthetic image and compare the noisy image quality after adding each noise using PSNR and SSIM. a. Gaussian Noise b. Rayleigh Noise c. Erlang(Gamma) Noise d. Exponential Noise e. Uniform Noise f. Impulse(salt & pepper) Noise 2. A dd periodic noise in an image and apply Butterworth band reject filters on this image and compare the quality after adding noise and after applying the filter using PSNR and SSIM 3. Take a gray scale image and add Gaussian noise. Write programs for following operations a. Arithmetic Mean filter b. Geo met r ic Mean filter c. Harmonic Mean filter d. Contraharmonic Mean filter 4. Take a gray scale image and add salt and pepper noise. Write programs for following operations a. Median filtering. b. Max filtering c. Min filtering d. Midpoint Filtering लैब - ७ (Lab - 7) 1. A dd periodic noise in an image and apply Butterworth bandpass filters on this image and extract the noise. Show the noise obtained and its Probability Density Function. 2. Write programs to perform following filtering operations on a gray scale image corrupted by impulse noise: a. Ideal Notch reject filter b. Gaussian Notch reject filter c. Butterworth Notch reject filter 3. Develop program to add different types of noise in a gray scale image and write functions to implement following filters for image restoration in presence of these noises a. Inverse filter b. Wiener filter मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) लैब - ८ (Lab - 8) 1. Develop program to implement point and line detection masks. Detect points and lines using appropriate masks for a given gray scale image. The lines detected will be of the following inclination: - a. 0 degree b. +45 degree c. - 45 degree d. 90 degrees 2. Apply first and second derivative on a gray scale image and show the results. What the first and second derivative refers in the image? 3. Develop programs for edge detection using different edge detection methods shown below: a. Sobel filter b. Prewitt filter c. Marr - Hildreth edge detection algorithm d. Canny algorithm 4. Given a set of coordinates as boundary pixels in an image. Write a program to implement Hough Transform for joining the points using different lines. लैब - ९ ( Lab 9 ) 1. Develop programs to achieve image segmentation using a. Basic Global thresholding b. Optimal global thresholding or Otsuʼs thresholding c. Basic Adaptive Thresholding 2. Write a program to perform Region Growing segmentation using a user - selected seed point and an intensity similarity threshold. Display the final segmented region. 3. Develop a program for Region Splitting using quadtree decomposition and apply a homogeneity test based on intensity variance. Display the final segmented image. 4. Perform morphological operations on a binary image using the following techniques: a. Dilation b. Erosion c. Opening (Erosion followed by Dilation) d. Closing (Dilation followed by Erosion) Use different structuring elements and compare the results. लैब - १० ( LAB 10) 1. Implement the following morphological algorithms on a binary image: a. Boundary Extraction b. Region Filling Use appropriate structuring elements and display the final outputs. मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) 2. Write a program to Implement the following morphological operations on a binary image: a. Connected Component Extraction b. Hit - or - Miss Transform c. Convex Hull d. Thinning e. Thickening Display final outputs for each operation. लैब - ११ ( LAB 11 ) 1. Given two different images (smooth and textured) C alculate their entropy, compression ratio, and data redundancy 2. Perform Huffman coding on an 8 x 8 synthetic image and s how: a. Probability table b. Huffman tree diagram c. Encoded bitstream 3. Using a small 4 x 4 matrix of values, perform manual arithmetic coding step - by - step: a. Compute cumulative ranges b. Encode sequence c. Decode to original sequence 4. Compress an image using both Huffman and Arithmetic coding, then analyze: a. Bitrate b. Entropy c. Encoding time d. Decoding time e. Compression ratio Prepare a comparative table and comment on which method is more efficient. लैब - १२ ( Lab - 12 ) 1. Write a program to implement LZW encoding and decoding for a grayscale image. Display the following: a. Initial dictionary b. Final dictionary c. Encoded output d. Compression ratio 2. Implement Run - Length Coding for a binary image and a grayscale image. Compare compression performance on both image types. 3. Generate all 8 bit - planes of a grayscale image. मौलाना आज़ाद रा*+,य .ौ/यो1गक4 सं7थान , भोपाल – 462003 MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL – 462003 क ं #ूटर िव*ान एवं अिभयांि1की िवभाग (Department of Computer Science and Engineering) a. Reconstruct the image using top 4 planes b. Measure reconstruction error (MSE, PSNR) 4. Implement Shannon - Fano coding for a grayscale image. Display: a. Probability table b. Code generation steps c. Final encoded output लैब - १३ ( Lab 13 ) 1. Write a program to compute and display the 2D DFT and Inverse DFT of a grayscale image.Show: a. Magnitude spectrum b. Log - transformed spectrum c. Phase spectrum 2. I mplement 2D DCT and Inverse DCT for an image. Show the DCT coefficient matrix and reconstructed image. 3. Apply wavelet decomposition using Haar wavelet transform and d isplay: a. Approximation (LL) b. Detail coefficients (LH, HL, HH) 4. Use wavelet transform detail coefficients (LH, HL, HH) for edge detection. Compare results with: a. Sobel b. Canny 5. For a medical image, apply: a. 2D DFT b. 2D DCT c. Wavelet transform Identify which domain is best for noise removal and diagnostic clarity. िवषय सम(यक (Subject Coordinators) िश<ण सहायक (Teacher Assistants ) डॉ %ोित भारती ( Dr. Jyoti Bharti ) PhD 6 - Chetna Indaurkar , PhD 1 9 - Aayushi Priya , PhD 26 - Rekha Meena (CSE - 1) , PhD 28 - Umesh Nayak , PhD 22 - T anveer Fatima Khan , PhD 23 - Rajesh Singh (CSE - 2), PhD 6 - Chetna Indaurkar , PhD 8 - Swapnil Murai , PhD 30 - Megha Sahu (CSE - 3) डॉ रमेश क ु मार ठाक ु र ( Dr. R amesh K umar Thakur ) Guest Faculty – AC ( CSE - 1 , CSE - 3 ) डॉ मेडीपेfी राम पवन ( Dr. Medipelly Ram Pawan )