Lossy image compression is a data encoding process that reduces the file size of a digital image by permanently discarding redundant or imperceptible visual information. Unlike lossless compression, which perfectly reconstructs the original pixel data, lossy compression achieves significantly higher compression ratios at the expense of an irreversible reduction in exact image fidelity. This technique typically uses mathematical transforms, quantization, and entropy coding—or modern machine learning architectures—to optimize the trade-off between bit rate and perceived visual quality, making it the standard approach for transmitting and storing digital photos across web platforms and consumer devices.
