Simultaneous fusion, compression, and encryption of multiple images.

Area of Science:

• Digital Image Processing
• Information Security
• Signal Processing

Background:

• Multiple image fusion and compression are critical for efficient data handling.
• Existing methods often lack robust security features for sensitive data.
• Spectral analysis offers unique opportunities for advanced image processing techniques.

Purpose of the Study:

• To develop a novel spectral multiple image fusion and compression analysis.
• To integrate a dual-layer encryption scheme for enhanced data security.
• To evaluate the method's performance against established compression standards.

Main Methods:

• Utilizing discrete cosine transform (DCT) for spectral image analysis.
• Implementing an adapted spectral quantization for optimized compression.
• Applying a two-level encryption: fusion/compression scheme and biometric data integration.
• Experimenting with grayscale image sequences.

Main Results:

• The proposed method achieves superior performance compared to the JPEG standard.
• Quantification of performance using Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR).
• Demonstrated viability for simultaneous compression and encryption of multiple images.

Conclusions:

• The developed spectral fusion and compression technique offers a robust solution for secure image data management.
• The integration of spectral analysis and biometric encryption enhances data security.
• The method presents a significant improvement over conventional image compression techniques.