Steganography, the art of concealing secret information within innocuous carriers, has gained significant attention in image processing. This review examines steganographic techniques, focusing on discrete wavelet transform (DWT) and Spread Spectrum Image Steganography (SSIS). It begins by discussing the fundamental concepts of steganography and its importance in security, digital forensics, and covert communication. The necessity for robust and imperceptible embedding techniques is emphasized to conceal secret data effectively. The mechanics of DWT are explored, highlighting its multi-resolution analysis capabilities that enhance security while minimizing perceptual distortion. Various DWT methodologies, such as LSB replacement and quantization, are evaluated for their strengths and weaknesses. The review also scrutinizes SSIS, which uses spread spectrum principles to achieve robust data hiding. Additionally, other mechanisms like Spatial LSB Embedding and Transform Domain Techniques are assessed based on embedding capacity, robustness, computational complexity, and perceptual quality. Ongoing experiments are being conducted to evaluate the effectiveness of these techniques. The review concludes by addressing challenges in steganography, including the detection of hidden information and security vulnerabilities, and emphasizes the need for ongoing research to adapt to evolving threats.