The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Compressive Sensing for Background Subtraction
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Distributed compressive video sensing
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Hash-based identification of sparse image tampering
IEEE Transactions on Image Processing
Distortion Estimation in Compressed Music Using Only Audio Fingerprints
IEEE Transactions on Audio, Speech, and Language Processing
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
Image information and visual quality
IEEE Transactions on Image Processing
Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs
IEEE Transactions on Image Processing
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In this paper, a new image hashing scheme satisfying robustness and security is proposed. We exploit the property of dimensionality reduction inherent in compressive sensing/sampling (CS) for image hash design. The gained benefits include (1) the hash size can be kept small and (2) the CS-based hash is computationally secure. We study the use of visual information fidelity (VIF) for hash comparison under Stirmark attacks. We further derive the relationships between the hash of an image and both of its MSE distortion and visual quality measured by VIF, respectively. Hence, based on hash comparisons, both the distortion and visual quality of a query image can be approximately estimated without accessing its original version. We also derive the minimum distortion for manipulating an image to be unauthentic to measure the security of our scheme.