Exploring the JPEG Algorithm

The JPEG algorithm is one of the most widely used methods for image compression, achieving substantial file size reduction by removing perceptually less significant information. Among its stages, quantization and frequency-domain transformation play a crucial role in determining the balance between visual quality and compression efficiency. This study explores structural modifications in both stages of the JPEG process: first, by testing alternative quantization matrices with varying levels of aggressiveness, and second, by replacing the standard DCT (Discrete Cosine Transform) with other mathematical transforms, such as Fourier, Laplace, and Wavelet. The results highlight how adjustments in quantization and transform selection can significantly influence the trade-off between efficiency and reconstructed image quality.