Lossless Image Data Compression Using Neural Networks

Image compression is an essential technique for reducing storage and transmission costs while preserving image quality. Traditional compression techniques often fail to achieve high efficiency without losing data. In this work, we propose a lossless image compression system using a Convolutional Neural Network (CNN) combined with residual encoding, Huffman coding, and AES encryption. The neural network predicts pixel values, and only the residual (difference) is encoded, significantly reducing redundancy. Huffman coding is applied for efficient compression, and AES encryption ensures secure storage. The system reconstructs the image perfectly without any loss of pixel information. Experimental results demonstrate efficient compression with exact reconstruction, making the system suitable for secure and real-time applications.