This chapter proposes an efficient image encryption and decryption algorithm designed for Internet of Things (IoT) applications, leveraging a combination of pseudo Hadamard transformation-based pixel transposition and 2D-Logistic map-based pixel value saturation. The algorithm addresses the challenges posed by strong inter-pixel correlation and large data capacity in IoT-based multimedia cryptosystems. The encryption and decryption processes are structured in two stages per round, ensuring enhanced security and resilience against cryptographic attacks. Experimental results using a dataset from the Computer Vision Group (CVG) demonstrate that the algorithm achieves a 96% pixel value difference between the host and cipher images, highlighting its effectiveness in securely transforming images. Moreover, the decryption process, even in the presence of various noises, maintains approximately 80% similarity between the decrypted and original host images, showcasing the algorithm’s robustness and practical applicability for securing IoT-based image data in real-world scenarios.