This project works with images and combines lossy and lossless compression techniques.

At first, the image is represented as a three-dimensional integer array, from which three two-dimensional arrays representing each of the color layers are extracted.

Then, two coefficients and an intercept are obtained using linear regression, so that the color values of the blue layer can be computed using only the red and green color layers.

In the red and green layers, similar values are then represented by their median. When iterating over the arrays, the frequencies of occurrence of each color shade in both layers are calculated.

The 256 color shades, for which the frequencies of occurrence are therefore known, serve as the "alphabet" for the Huffman tree construction. This makes it possible to create a dictionary and the original data is translated into binary code, then into an array of bytes, then into characters and stored in a file. The necessary information needed for decompression (color frequencies, regression coefficients, etc.) is also stored.

This work also includes a decompression algorithm that allows the image to be reconstructed. Clearly, due to the use of lossy compression techniques, the exact original image can no longer be restored.