/multimedia-projects

Mini-projects created as part of the Multimedia Fundamentals course.

Primary LanguageJupyter Notebook

Multimedia Projects

Łukasz Staniszewski

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ENG: This repository contains mini-projects created as part of the Multimedia Fundamentals course.

Table of contents

  1. Signals
    • Task 1 - Determining the amplitude and phase spectrum, calculating the signal power and check the Parseval theorem. Checking the validity of the discrete Fourier transform theorem of circular convolution of signals.
    • Task 2 - Investigating the effect of time shift on the form of the amplitude spectrum and phase spectrum of a discrete harmonic signal.
    • Task 3 - Investigating the effect of zero padding on the form of the amplitude spectrum and phase spectrum of a discrete signal.
    • Task 4 - Plotting the power spectral density graph of the real signal assuming a specific number of samples. Determining whether spectral leakage occurs for a given number of samples.
    [PL] DOCUMENTATION HERE [PL]
  2. Image filtering
    • Task 1 - Performing colour filtering operations on a noisy digital image. Processing with a smoothing filter (Gaussian) and a median filter. Calculation of PSNR.
    • Task 2 - Implementation of a histogram equalisation operation for a colour image. Convert an RGB image to a YCbCr image. Comparison of images and their histograms.
    • Task 3 - Using the Laplace filter to determine the high-frequency components of the image. Image sharpening.
    [PL] DOCUMENTATION HERE [PL]
  3. Image statistical properties
    • Task 1 - Determination of bit rate for monochromatic image compressed with PNG encoder, determination of image entropy.
    • Task 2 - Determining and displaying differential monochromatic image. Determining its histogram and entropy and comparing it with the original image.
    • Task 3 - Determination of DWT transformation coefficients - determination and display of bands for monochromatic image.
    • Task 4 - Calculating entropy for the RGB components of the colour image.
    • Task 5 - Performing conversion from RGB to YUV and calculate the entropy for the YUV components. Determining histograms for all components.
    • Task 6 - Determining dependence of distortion D on bit rate R (relative to image quality) with distortion measure PSNR and error mean square error MSE. Comparing compression ratios obtained for the JPEG encoder with the PNG encoder.
    [PL] DOCUMENTATION HERE [PL]
  4. Image analysis - face detection
    • Task 1 - Determining the performance measure of face detection algorithms: HAAR'S CASCADE DETECTOR, HOG + SVM and CNN (MMOD) for a test image.
    • Task 2 - Applying modifications to the face detection algorithms and measuring their execution times.
    [PL] DOCUMENTATION HERE [PL]
  5. Graphics generation using OpenGL
    • Task 1 - Creation of a basic program and fragment shader in order to generate the Mandelbrot fractal.
    • Task 2 - Assembling object transformations in a 3D scene. Loading objects from files, creating objects and applying a series of transformations to them to build a 'robot'.
    • Task 3 - Adding Phong shading to a programme with a single light source, taking into account the parameters: light position and colour, object colour and object glossiness.
    [PL] DOCUMENTATION HERE [PL]

Used technologies

  1. Python 3.10
  2. Necessary Python packages in requirements.txt