ImageCompression

Image Compression is done using Discrete Cosine Transform and Inverse Discrete Cosine Transform.

This code reads an image as a matrix and applies discrete cosine transform on it. Then, user needs to enter the quality factor he/she want for the compressed image. Predefined quantification matrix does the job of quantifying the image after dct. Now, we just need to get back into our original space of pixels by applying inverse discrete cosine transform. The image we get is compressed image with quality factor user has entered.

Concepts of Signals and Systems and Linear Algebra are applied together to get desired output which actually was essential part of this project.

P.S.: This is just the software based approach to image compression with dct-idct. You can also implement whole simulation on FPGA with verilog coding which was our real project. You need to take care of number of multiplications while coding in verilog which will lead you to understand and apply fft's butterfly structure to transform image pixels to frequency domain.