This paper provides an overview of image encryption algorithms and evaluation metrics, aiming to help researchers and practitioners understand the current state of image encryption. The authors classify image encryption into seven approaches: traditional ciphers, chaotic systems, DNA encoding, neural networks, compressive sensing, frequency domain, and meaningful encryption. Each approach is analyzed for its strengths and weaknesses. The paper also reviews a comprehensive set of security, quality, and efficiency evaluation metrics, including correlation coefficient, histogram analysis, entropy, mean square error (MSE), and the NIST SP 800-22 Test. Upper and lower bounds for these metrics are provided. The pros and cons of different image encryption approaches and their suitability for various applications are discussed. The main contributions of the paper include the classification of image encryption approaches, a detailed review of evaluation metrics, and the calculation of upper and lower bounds for these metrics.This paper provides an overview of image encryption algorithms and evaluation metrics, aiming to help researchers and practitioners understand the current state of image encryption. The authors classify image encryption into seven approaches: traditional ciphers, chaotic systems, DNA encoding, neural networks, compressive sensing, frequency domain, and meaningful encryption. Each approach is analyzed for its strengths and weaknesses. The paper also reviews a comprehensive set of security, quality, and efficiency evaluation metrics, including correlation coefficient, histogram analysis, entropy, mean square error (MSE), and the NIST SP 800-22 Test. Upper and lower bounds for these metrics are provided. The pros and cons of different image encryption approaches and their suitability for various applications are discussed. The main contributions of the paper include the classification of image encryption approaches, a detailed review of evaluation metrics, and the calculation of upper and lower bounds for these metrics.