JPEG Image Compression Using Multiple Core Strategy in FPGA achieving High Peak Signal to Noise Ratios

Anjum, Umar; Hussain, Arif; Ali, Channa Babar; Afzal, Umer; Hussain, Ibrar; Noorwali, Abdulfattah; Shah, Syed Aziz

doi:10.1109/icoten52080.2021.9493460

Cited by 1 publication

(1 citation statement)

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“…Where MAX is the maximum possible pixel value of the image, this metric describes the proportion of a signal's maximal strength to the power of corrupting noise that compromises the accuracy of its representation. This metric determines signal reconstruction quality, like video coding and data encoding [25].…”

Section: Related Workmentioning

confidence: 99%

Image Steganography Using LSB and Hybrid Encryption Algorithms

Alanzy,

Alomrani,

Alqarni

et al. 2023

Applied Sciences

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In today’s era of widespread web technology and cloud computing, ensuring data security has become a crucial concern across various industries. Instances of data breaches and vulnerabilities in cloud storage have emphasized the need for robust data protection and communication protocols, particularly in sectors like social media, military, and research. This research proposes a Multi-Level Steganography (MLS) algorithm that employs two encryption algorithms, AES and Blow-Fish, to secure the cover image and embed encryption keys as key images within the stego image. The proposed MLS algorithm incorporates a robust pixel randomization function to enhance the security of the encrypted data. Experimental results demonstrate that the proposed algorithm effectively protects data with high Peak Signal-to-Noise Ratio (PSNR) and low Mean Square Error (MSE) values, ensuring superior image quality, reliable encryption, and decryption of secret messages. The utilization of hybrid encryption with AES and BlowFish algorithms further strengthens the algorithm’s security by augmenting the complexity of the encryption process.

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Section: Related Workmentioning

confidence: 99%