Unlocking Image Compression with Discrete Cosine Transform (DCT) 📸

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Hello Viewers, in this video, Discrete Cosine Transform (DCT)of images is introduced. A brief theoretical background of DCT is highlighted along with its application to image compression.
Also its basic properties, advantages and disadvantages are also discussed.
Mathematical equations are also explained for forward DCT and inverse DCT and basis functions are also discussed. MATLAB codes are also given for basis function generation, image compression using dct2( ) and dctmtx( ).

This video has following contents:

* Discrete Cosine Transform. Its applications, Advantages and Disadvantages.
* Computing 2D FDCT, IDCT and DCT basis functions.
* MATLAB Code for 2D-DCT basis functions.
* DCT computation methods (DCT using FFT and DCT using transformation matrix).
* Image Compression using DCT.
* MATLAB Code for image compression using dct2( ).
* MATLAB Code for image compression using dctmtx( ) and block processing.

Links of previous videos:
1. Wavelet Transform Analysis of Images using MATLAB and SIMULINK: https://youtu.be/efCrlfYewWQ
2. Wavelet Transform Analysis of Images using Python: https://youtu.be/JdVq8Tn1ds0