Image Data Hiding Using Steganography

This source code is developed in MATLAB based on steganography principles. Steganography allows concealment of various data formats, including images, within another carrier image. The methodology is specifically designed for medical data applications, providing a secure way to transmit sensitive information without raising suspicion. Steganography represents a data hiding technique that facilitates secure transmission and storage of confidential information while maintaining apparent innocence. It serves critical roles in personal privacy protection and covert communication systems. The implemented MATLAB solution employs a sophisticated steganographic approach for image embedding, where secret images are encoded into cover images using pixel manipulation algorithms. Key implementation features include: - LSB (Least Significant Bit) modification for minimal visual impact - Color channel separation and processing for RGB images - Embedding capacity optimization algorithms - Error-checking mechanisms for data integrity The core functionality utilizes MATLAB's image processing toolbox for pixel-level operations, including imread() for image input, bitget()/bitset() functions for bit-plane manipulation, and imwrite() for generating the steganographed output. The algorithm maintains the original image dimensions while embedding payload data through strategic bit replacement in the host image's pixel values. This technique achieves confidential transmission by ensuring the embedded data remains visually undetectable while maintaining full recoverability through proper extraction procedures. The medical application focus ensures compliance with data sensitivity requirements through robust embedding strategies.